1D Convolution을 기본 구성 요소로 하는 EEG classifier를 학습해보는 노트북.
# for auto-reloading external modules
# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython
%load_ext autoreload
%autoreload 2
# Load some packages
import os
import glob
import json
from copy import deepcopy
import datetime
import matplotlib.pyplot as plt
import pprint
from IPython.display import clear_output
from tqdm.auto import tqdm
import numpy as np
import random
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader
from torchvision import transforms
from typing import Type, Any, Callable, Union, List, Optional
# custom package
from utils.eeg_dataset import *
# Other settings
%matplotlib inline
%config InlineBackend.figure_format = 'retina' # cleaner text
plt.style.use('default')
# ['Solarize_Light2', '_classic_test_patch', 'bmh', 'classic', 'dark_background', 'fast',
# 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn', 'seaborn-bright', 'seaborn-colorblind',
# 'seaborn-dark', 'seaborn-dark-palette', 'seaborn-darkgrid', 'seaborn-deep', 'seaborn-muted',
# 'seaborn-notebook', 'seaborn-paper', 'seaborn-pastel', 'seaborn-poster', 'seaborn-talk',
# 'seaborn-ticks', 'seaborn-white', 'seaborn-whitegrid', 'tableau-colorblind10']
plt.rcParams['image.interpolation'] = 'nearest'
plt.rcParams["font.family"] = 'NanumGothic' # for Hangul in Windows
print('PyTorch version:', torch.__version__)
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
if torch.cuda.is_available(): print('cuda is available.')
else: print('cuda is unavailable.')
PyTorch version: 1.7.1 cuda is available.
# Data file path
root_path = r'dataset/02_Curated_Data/'
# Checkpoint
save_checkpoint = True
meta_path = os.path.join(root_path, 'metadata_debug.json')
with open(meta_path, 'r') as json_file:
metadata = json.load(json_file)
pprint.pprint(metadata[0])
{'age': 78,
'birth': '1940-06-02',
'dx1': 'mci_rf',
'edfname': '00001809_261018',
'events': [[0, 'Start Recording'],
[0, 'New Montage - Montage 002'],
[36396, 'Eyes Open'],
[72518, 'Eyes Closed'],
[73862, 'Eyes Open'],
[75248, 'Eyes Closed'],
[76728, 'swallowing'],
[77978, 'Eyes Open'],
[79406, 'Eyes Closed'],
[79996, 'Photic On - 3.0 Hz'],
[80288, 'Eyes Open'],
[81296, 'Eyes Closed'],
[82054, 'Photic Off'],
[84070, 'Photic On - 6.0 Hz'],
[84488, 'Eyes Open'],
[85538, 'Eyes Closed'],
[86086, 'Photic Off'],
[88144, 'Photic On - 9.0 Hz'],
[90160, 'Photic Off'],
[91458, 'Eyes Open'],
[92218, 'Photic On - 12.0 Hz'],
[92762, 'Eyes Closed'],
[94198, 'Photic Off'],
[94742, 'Eyes Open'],
[95708, 'Eyes Closed'],
[96256, 'Photic On - 15.0 Hz'],
[98272, 'Photic Off'],
[100330, 'Photic On - 18.0 Hz'],
[102346, 'Photic Off'],
[102596, 'Eyes Open'],
[103856, 'Eyes Closed'],
[104361, 'Photic On - 21.0 Hz'],
[106420, 'Photic Off'],
[106880, 'Eyes Open'],
[107804, 'Eyes Closed'],
[108435, 'Photic On - 24.0 Hz'],
[110452, 'Photic Off'],
[111080, 'Eyes Open'],
[112004, 'Eyes Closed'],
[112509, 'Photic On - 27.0 Hz'],
[114528, 'Photic Off'],
[114864, 'Eyes Open'],
[116124, 'Eyes Closed'],
[116544, 'Photic On - 30.0 Hz'],
[118602, 'Photic Off'],
[126672, 'artifact'],
[134030, 'Move'],
[135584, 'Eyes Open'],
[136668, 'Eyes Closed'],
[139818, 'Eyes Open'],
[141414, 'Eyes Closed'],
[145000, 'Paused']],
'label': ['mci', 'mci_amnestic', 'mci_amnestic_rf'],
'record': '2018-10-26T15:46:26',
'serial': '00001'}
diagnosis_filter = [
# Normal
{'type': 'Normal',
'include': ['normal'],
'exclude': []},
# Non-vascular MCI
{'type': 'MCI or Dementia',
'include': ['mci', 'dementia'],
'exclude': []},
]
def generate_class_label(label):
for c, f in enumerate(diagnosis_filter):
# inc = set(f['include']) & set(label) == set(f['include'])
inc = len(set(f['include']) & set(label)) > 0
exc = len(set(f['exclude']) & set(label)) == 0
if inc and exc:
return (c, f['type'])
return (-1, 'The others')
class_label_to_type = [d_f['type'] for d_f in diagnosis_filter]
print('class_label_to_type:', class_label_to_type)
class_label_to_type: ['Normal', 'MCI or Dementia']
splitted_metadata = [[] for i in diagnosis_filter]
for m in metadata:
c, n = generate_class_label(m['label'])
if c >= 0:
m['class_type'] = n
m['class_label'] = c
splitted_metadata[c].append(m)
for i, split in enumerate(splitted_metadata):
if len(split) == 0:
print(f'(Warning) Split group {i} has no data.')
else:
print(f'- There are {len(split):} data belonging to {split[0]["class_type"]}')
- There are 463 data belonging to Normal - There are 724 data belonging to MCI or Dementia
# random seed
random.seed(0)
# Train : Val : Test = 8 : 1 : 1
ratio1 = 0.8
ratio2 = 0.1
metadata_train = []
metadata_val = []
metadata_test = []
for split in splitted_metadata:
random.shuffle(split)
n1 = round(len(split) * ratio1)
n2 = n1 + round(len(split) * ratio2)
metadata_train.extend(split[:n1])
metadata_val.extend(split[n1:n2])
metadata_test.extend(split[n2:])
random.shuffle(metadata_train)
random.shuffle(metadata_val)
random.shuffle(metadata_test)
print('Train data size\t\t:', len(metadata_train))
print('Validation data size\t:', len(metadata_val))
print('Test data size\t\t:', len(metadata_test))
print('\n', '--- Recheck ---', '\n')
train_class_nums = np.zeros((len(class_label_to_type)), dtype=np.int32)
for m in metadata_train:
train_class_nums[m['class_label']] += 1
val_class_nums = np.zeros((len(class_label_to_type)), dtype=np.int32)
for m in metadata_val:
val_class_nums[m['class_label']] += 1
test_class_nums = np.zeros((len(class_label_to_type)), dtype=np.int32)
for m in metadata_test:
test_class_nums[m['class_label']] += 1
print('Train data label distribution\t:', train_class_nums, train_class_nums.sum())
print('Val data label distribution\t:', val_class_nums, val_class_nums.sum())
print('Test data label distribution\t:', test_class_nums, test_class_nums.sum())
# random seed
random.seed()
# print([m['serial'] for m in metadata_train[:15]])
# print([m['serial'] for m in metadata_val[:15]])
# print([m['serial'] for m in metadata_test[:15]])
Train data size : 949 Validation data size : 118 Test data size : 120 --- Recheck --- Train data label distribution : [370 579] 949 Val data label distribution : [46 72] 118 Test data label distribution : [47 73] 120
ages = []
for m in metadata_train:
ages.append(m['age'])
ages = np.array(ages)
age_mean = np.mean(ages)
age_std = np.std(ages)
print('Age mean and standard deviation:')
print(age_mean, age_std)
Age mean and standard deviation: 71.20758693361434 9.797857089966335
composed = transforms.Compose([EEGNormalizeAge(mean=age_mean, std=age_std),
EEGDropPhoticChannel(),
EEGRandomCrop(crop_length=200*10), # 10 sec
EEGNormalizePerSignal(),
EEGToTensor()])
train_dataset = EEGDataset(root_path, metadata_train, composed)
val_dataset = EEGDataset(root_path, metadata_val, composed)
test_dataset = EEGDataset(root_path, metadata_test, composed)
print(train_dataset[0]['signal'].shape)
print(train_dataset[0])
print()
print('-' * 100)
print()
print(val_dataset[0]['signal'].shape)
print(val_dataset[0])
print()
print('-' * 100)
print()
print(test_dataset[0]['signal'].shape)
print(test_dataset[0])
torch.Size([20, 2000])
{'signal': tensor([[-0.2622, -0.4226, -0.5028, ..., -1.6255, -1.5453, -1.4651],
[-1.2972, -1.4482, -1.4482, ..., -1.4482, -1.4482, -1.1462],
[ 0.0336, -0.2786, -0.9030, ..., -0.7469, -1.0591, -1.0591],
...,
[-0.0555, -0.7934, -1.9001, ..., -0.2400, -0.0555, 0.1289],
[ 0.3004, -0.0905, -0.8724, ..., 1.2778, 1.8642, 1.8642],
[ 0.5496, 0.4864, 0.3996, ..., -0.1612, -0.1928, -0.2007]]), 'age': tensor(0.1829), 'class_label': tensor(1), 'metadata': {'serial': '01315', 'edfname': '01379199_220618', 'birth': '1945-01-07', 'record': '2018-06-22T08:55:30', 'age': 73, 'dx1': 'load', 'label': ['dementia', 'ad', 'load'], 'events': [[0, 'Start Recording'], [0, 'New Montage - Montage 002'], [15941, 'artifact'], [36936, 'Eyes Open'], [37744, 'artifact'], [70640, 'Eyes Closed'], [72388, 'Eyes Open'], [73608, 'Eyes Closed'], [76388, 'Eyes Open'], [78566, 'Eyes Closed'], [80202, 'Photic On - 3.0 Hz'], [80544, 'Eyes Open'], [81164, 'Eyes Closed'], [81806, 'artifact'], [82218, 'Photic Off'], [84280, 'Photic On - 6.0 Hz'], [86296, 'Photic Off'], [86580, 'Eyes Open'], [87810, 'Eyes Closed'], [88102, 'artifact'], [88314, 'Photic On - 9.0 Hz'], [90330, 'Photic Off'], [92388, 'Photic On - 12.0 Hz'], [94404, 'Photic Off'], [94788, 'artifact'], [95832, 'Awake'], [96462, 'Photic On - 15.0 Hz'], [98478, 'Photic Off'], [100500, 'Photic On - 18.0 Hz'], [102516, 'Photic Off'], [104574, 'Photic On - 21.0 Hz'], [106590, 'Photic Off'], [106883, 'Eyes Open'], [107976, 'Eyes Closed'], [108606, 'Photic On - 24.0 Hz'], [110664, 'Photic Off'], [112680, 'Photic On - 27.0 Hz'], [114696, 'Photic Off'], [116754, 'Photic On - 30.0 Hz'], [118770, 'Photic Off'], [118932, 'artifact'], [120409, 'Eyes Open'], [121524, 'artifact'], [122594, 'Eyes Closed'], [126800, 'Paused']], 'class_type': 'MCI or Dementia', 'class_label': 1}}
----------------------------------------------------------------------------------------------------
torch.Size([20, 2000])
{'signal': tensor([[-0.1877, -0.1957, -0.2010, ..., -1.8883, -1.8989, -1.9176],
[ 0.9318, 1.0977, 1.0977, ..., -0.8931, -0.8378, -0.8378],
[ 0.9605, 1.1771, 1.6101, ..., 0.0944, 0.7440, 0.9605],
...,
[ 0.2970, 0.5910, 0.8850, ..., 1.9141, 2.3551, 2.7961],
[ 0.2231, 0.3580, 0.3580, ..., 2.2472, 2.7869, 3.0568],
[ 0.4906, 0.3999, 0.3394, ..., 1.2771, 1.1863, 1.1258]]), 'age': tensor(-2.2666), 'class_label': tensor(0), 'metadata': {'serial': '00754', 'edfname': '01035046_020715', 'birth': '1965-09-15', 'record': '2015-07-02T13:20:15', 'age': 49, 'dx1': 'cb_normal', 'label': ['normal', 'cb_normal'], 'events': [[0, 'Start Recording'], [0, 'New Montage - Montage 002'], [462, 'Eyes Open'], [6090, 'Eyes Closed'], [12348, 'Eyes Open'], [19320, 'Eyes Closed'], [24822, 'Eyes Open'], [30239, 'Eyes Closed'], [36330, 'Eyes Open'], [42294, 'Eyes Closed'], [53340, 'Eyes Open'], [54138, 'Eyes Closed'], [62286, 'Eyes Open'], [66234, 'Eyes Closed'], [72240, 'Eyes Open'], [79800, 'Eyes Closed'], [85260, 'Eyes Open'], [93996, 'Eyes Closed'], [102102, 'Eyes Closed'], [107730, 'Eyes Open'], [113861, 'Eyes Closed'], [120600, 'Paused']], 'class_type': 'Normal', 'class_label': 0}}
----------------------------------------------------------------------------------------------------
torch.Size([20, 2000])
{'signal': tensor([[ 0.0062, -0.0128, -0.0191, ..., 0.9455, 0.9455, 0.9328],
[-0.0837, -0.0837, -0.1406, ..., -0.2543, -0.1406, -0.1975],
[-0.3594, -0.3594, -0.2465, ..., -0.2465, -0.2465, -0.3594],
...,
[ 1.2682, 1.4674, 1.6665, ..., -0.9226, -1.1218, -1.1218],
[ 0.1531, 0.3737, 0.5943, ..., 0.1531, 0.1531, -0.0675],
[-0.1850, -0.2098, -0.1353, ..., 0.8709, 0.5480, 0.3616]]), 'age': tensor(1.6118), 'class_label': tensor(1), 'metadata': {'serial': '01183', 'edfname': '01303198_020317', 'birth': '1929-10-31', 'record': '2017-03-02T14:10:12', 'age': 87, 'dx1': 'mci retrieval failure', 'label': ['mci', 'mci_amnestic', 'mci_amnestic_rf'], 'events': [[0, 'Start Recording'], [0, 'New Montage - Montage 002'], [1444, 'Eyes Open'], [6106, 'Eyes Closed'], [12196, 'Eyes Open'], [17994, 'Eyes Closed'], [24126, 'Eyes Open'], [30177, 'Eyes Closed'], [36226, 'Eyes Open'], [42022, 'Eyes Closed'], [48952, 'Eyes Open'], [54790, 'Eyes Closed'], [60166, 'Eyes Open'], [66256, 'Eyes Closed'], [73774, 'Eyes Open'], [78016, 'Eyes Closed'], [84192, 'Eyes Open'], [90198, 'Eyes Closed'], [95754, 'Move'], [96372, 'Eyes Open'], [101798, 'A2 Recheck'], [101800, 'Paused'], [110200, 'Recording Resumed'], [112416, 'Eyes Closed'], [116448, 'Eyes Open'], [122332, 'Eyes Closed'], [130359, 'Eyes Open'], [131746, 'Eyes Closed'], [132796, 'Photic On - 3.0 Hz'], [133510, 'Eyes Open'], [134224, 'Eyes Closed'], [134812, 'Photic Off'], [136870, 'Photic On - 6.0 Hz'], [137416, 'Eyes Open'], [138298, 'Eyes Closed'], [138886, 'Photic Off'], [140944, 'Photic On - 9.0 Hz'], [141574, 'Eyes Open'], [142330, 'Eyes Closed'], [142960, 'Photic Off'], [144976, 'Photic On - 12.0 Hz'], [145564, 'Eyes Open'], [146320, 'Eyes Closed'], [146992, 'Photic Off'], [149050, 'Photic On - 15.0 Hz'], [151066, 'Photic Off'], [153124, 'Photic On - 18.0 Hz'], [153712, 'Eyes Open'], [154510, 'Eyes Closed'], [155140, 'Photic Off'], [157156, 'Photic On - 21.0 Hz'], [159172, 'Photic Off'], [161230, 'Photic On - 24.0 Hz'], [163246, 'Photic Off'], [163540, 'Eyes Open'], [164464, 'Eyes Closed'], [165304, 'Photic On - 27.0 Hz'], [167320, 'Photic Off'], [169336, 'Photic On - 30.0 Hz'], [171352, 'Photic Off'], [171772, 'Eyes Open'], [173452, 'Eyes Closed'], [181474, 'Eyes Open'], [183196, 'Eyes Closed'], [185200, 'Paused']], 'class_type': 'MCI or Dementia', 'class_label': 1}}
print('Current PyTorch device:', device)
if device.type == 'cuda':
num_workers = 0 # A number other than 0 causes an error
pin_memory = True
else:
num_workers = 0
pin_memory = False
train_loader = DataLoader(train_dataset,
batch_size=32,
shuffle=True,
drop_last=True,
num_workers=num_workers,
pin_memory=pin_memory,
collate_fn=eeg_collate_fn)
for i_batch, sample_batched in enumerate(train_loader):
sample_batched['signal'].to(device)
sample_batched['age'].to(device)
sample_batched['class_label'].to(device)
print(i_batch,
sample_batched['signal'].shape,
sample_batched['age'].shape,
sample_batched['class_label'].shape,
len(sample_batched['metadata']))
if i_batch > 3:
break
Current PyTorch device: cuda 0 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32 1 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32 2 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32 3 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32 4 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32
train_loader = DataLoader(train_dataset,
batch_size=32,
shuffle=True,
drop_last=True,
num_workers=num_workers,
pin_memory=pin_memory,
collate_fn=eeg_collate_fn)
val_loader = DataLoader(val_dataset,
batch_size=32,
shuffle=False,
drop_last=False,
num_workers=num_workers,
pin_memory=pin_memory,
collate_fn=eeg_collate_fn)
test_loader = DataLoader(test_dataset,
batch_size=32,
shuffle=False,
drop_last=False,
num_workers=num_workers,
pin_memory=pin_memory,
collate_fn=eeg_collate_fn)
from torch.utils.tensorboard import SummaryWriter
import ipynbname
nb_fname = ipynbname.name()
def count_parameters(model):
return sum(p.numel() for p in model.parameters() if p.requires_grad)
def visualize_network_tensorboard(model, name):
# default `log_dir` is "runs" - we'll be more specific here
writer = SummaryWriter('runs/' + nb_fname + '_' + name)
for batch_i, sample_batched in enumerate(train_loader):
# pull up the batch data
x = sample_batched['signal'].to(device)
age = sample_batched['age'].to(device)
target = sample_batched['class_label'].to(device)
# apply model on whole batch directly on device
writer.add_graph(model, (x, age))
output = model(x, age, print_shape=True)
break
writer.close()
def train_one_epoch(model, optimizer, log_interval):
# turn the models to training mode
model.train()
losses = []
correct, total = (0, 0)
C = len(class_label_to_type)
train_confusion = np.zeros((C, C), dtype=np.int32)
for batch_i, sample_batched in enumerate(train_loader):
# pull up the batch data
x = sample_batched['signal'].to(device)
age = sample_batched['age'].to(device)
target = sample_batched['class_label'].to(device)
# apply model on whole batch directly on device
output = model(x, age)
# negative log-likelihood for a tensor of size (batch x n_output)
pred = F.log_softmax(output, dim=1)
loss = F.nll_loss(pred, target)
# backprop and update
loss.backward()
optimizer.step()
optimizer.zero_grad()
# record loss
losses.append(loss.item())
# train accuracy
pred = pred.argmax(dim=-1)
correct += pred.squeeze().eq(target).sum().item()
total += pred.shape[0]
# confusion matrix
train_confusion += calculate_confusion_matrix(pred, target)
# print training stats
if log_interval is not None and (batch_i + 1) % log_interval == 0:
print(f'- Iter {batch_i + 1:03d} / {len(train_loader):03d}, Loss: {loss.item():.06f}')
train_accuracy = 100.0 * correct / total
return (losses, train_accuracy, train_confusion)
def check_val_accuracy(model, repeat=1):
model.eval()
correct, total = (0, 0)
C = len(class_label_to_type)
val_confusion = np.zeros((C, C), dtype=np.int32)
for k in range(repeat):
for sample_batched in val_loader:
# pull up the data
x = sample_batched['signal'].to(device)
age = sample_batched['age'].to(device)
target = sample_batched['class_label'].to(device)
# apply model on whole batch directly on device
output = model(x, age)
pred = F.log_softmax(output, dim=1)
# val accuracy
pred = pred.argmax(dim=-1)
correct += pred.squeeze().eq(target).sum().item()
total += pred.shape[0]
# confusion matrix
val_confusion += calculate_confusion_matrix(pred, target)
val_accuracy = 100.0 * correct / total
return (val_accuracy, val_confusion)
def check_test_accuracy(model, repeat=1):
model.eval()
correct, total = (0, 0)
C = len(class_label_to_type)
test_confusion = np.zeros((C, C), dtype=np.int32)
test_debug = {data['metadata']['serial']:
{'GT': data['class_label'].item(),
'Acc': 0,
'Pred': [0] * C} for data in test_dataset}
for k in range(repeat):
for sample_batched in test_loader:
# pull up the data
x = sample_batched['signal'].to(device)
age = sample_batched['age'].to(device)
target = sample_batched['class_label'].to(device)
# apply model on whole batch directly on device
output = model(x, age)
pred = F.log_softmax(output, dim=1)
# test accuracy
pred = pred.argmax(dim=-1)
correct += pred.squeeze().eq(target).sum().item()
total += pred.shape[0]
# confusion matrix
test_confusion += calculate_confusion_matrix(pred, target)
# test debug
for n in range(pred.shape[0]):
serial = sample_batched['metadata'][n]['serial']
test_debug[serial]['edfname'] = sample_batched['metadata'][n]['edfname']
test_debug[serial]['Pred'][pred[n].item()] += 1
acc = test_debug[serial]['Pred'][target[n].item()] / np.sum(test_debug[serial]['Pred']) * 100
test_debug[serial]['Acc'] = f'{acc:>6.02f}%'
test_accuracy = 100.0 * correct / total
return (test_accuracy, test_confusion, test_debug)
def calculate_confusion_matrix(pred, target):
N = target.shape[0]
C = len(class_label_to_type)
confusion = np.zeros((C, C), dtype=np.int32)
for i in range(N):
r = target[i]
c = pred[i]
confusion[r, c] += 1
return confusion
def draw_loss_plot(loss_history):
plt.style.use('default') # default, ggplot, fivethirtyeight, classic
fig = plt.figure(num=1, clear=True, figsize=(15.0, 6.0), constrained_layout=True)
ax = fig.add_subplot(1, 1, 1)
ax.plot(loss_history)
ax.vlines(0, 0, 1, transform=ax.get_xaxis_transform(), colors='k', alpha=0.1)
for e in range(1, n_epoch + 1):
if e % lr_schedule_step == 0:
ax.vlines(e*len(train_loader) - 1, 0, 1, transform=ax.get_xaxis_transform(), colors='m', alpha=0.3)
else:
ax.vlines(e*len(train_loader) - 1, 0, 1, transform=ax.get_xaxis_transform(), colors='k', alpha=0.1)
ax.set_title('Loss Plot')
ax.set_xlabel('Iteration')
ax.set_ylabel('Training Loss')
plt.show()
fig.clear()
plt.close(fig)
def draw_accuracy_history(train_acc_history, val_acc_history):
plt.style.use('default') # default, ggplot, fivethirtyeight, classic
fig = plt.figure(num=1, clear=True, figsize=(15.0, 6.0), constrained_layout=True)
ax = fig.add_subplot(1, 1, 1)
ax.plot(train_acc_history, 'r-', label='Train accuracy')
ax.plot(val_acc_history, 'b-', label='Validation accuracy')
ax.legend(loc='lower right')
ax.set_title('Accuracy Plot during Training')
ax.set_xlabel('Epoch')
ax.set_ylabel('Accuracy (%)')
plt.show()
fig.clear()
plt.close(fig)
def draw_confusion(confusion):
C = len(class_label_to_type)
plt.style.use('default') # default, ggplot, fivethirtyeight, classic
plt.rcParams['image.cmap'] = 'jet' # 'nipy_spectral'
fig = plt.figure(num=1, clear=True, figsize=(5.0, 5.0), constrained_layout=True)
ax = fig.add_subplot(1, 1, 1)
im = ax.imshow(confusion, alpha=0.8)
ax.set_xticks(np.arange(C))
ax.set_yticks(np.arange(C))
ax.set_xticklabels(class_label_to_type)
ax.set_yticklabels(class_label_to_type)
for r in range(C):
for c in range(C):
text = ax.text(c, r, confusion[r, c],
ha="center", va="center", color='k')
ax.set_title('Confusion Matrix')
ax.set_xlabel('Prediction')
ax.set_ylabel('Ground Truth')
plt.setp(ax.get_xticklabels(), rotation=45, ha="right", rotation_mode="anchor")
plt.show()
fig.clear()
plt.close(fig)
def learning_rate_search(model, min_log_lr, max_log_lr, trials, epochs):
learning_rate_record = []
for t in tqdm(range(trials)):
log_lr = np.random.uniform(min_log_lr, max_log_lr)
lr = 10 ** log_lr
model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=0.0001)
for e in range(epochs):
_, train_accuracy, _ = train_one_epoch(model, optimizer, log_interval=None)
# Train accuracy for the final epoch is stored
learning_rate_record.append((log_lr, train_accuracy))
return learning_rate_record
def draw_learning_rate_record(learning_rate_record):
plt.style.use('default') # default, ggplot, fivethirtyeight, classic
fig = plt.figure(num=1, clear=True, figsize=(8.0, 8.0), constrained_layout=True)
ax = fig.add_subplot(1, 1, 1)
ax.set_title('Learning Rate Search')
ax.set_xlabel('Learning rate in log-scale')
ax.set_ylabel('Train accuracy')
for log_lr, val_accuracy in learning_rate_record:
ax.scatter(log_lr, val_accuracy, c='r',
alpha=0.5, edgecolors='none')
plt.show()
fig.clear()
plt.close(fig)
class TinyNet(nn.Module):
def __init__(self, n_input=20, n_output=3, stride=7, n_channel=64,
use_age=True, final_pool='average'):
super().__init__()
if final_pool not in {'average', 'max'}:
raise ValueError("final_pool must be set to one of ['average', 'max']")
self.use_age = use_age
self.conv1 = nn.Conv1d(n_input, n_channel, kernel_size=35, stride=stride)
self.bn1 = nn.BatchNorm1d(n_channel)
self.pool1 = nn.MaxPool1d(4)
self.conv2 = nn.Conv1d(n_channel, n_channel, kernel_size=7)
self.bn2 = nn.BatchNorm1d(n_channel)
self.pool2 = nn.MaxPool1d(2)
if final_pool == 'average':
self.final_pool = nn.AdaptiveAvgPool1d(1)
elif final_pool == 'max':
self.final_pool = nn.AdaptiveMaxPool1d(1)
if self.use_age:
self.fc1 = nn.Linear(n_channel + 1, n_channel)
else:
self.fc1 = nn.Linear(n_channel, n_channel)
self.dropout = nn.Dropout(p=0.3)
self.bnfc1 = nn.BatchNorm1d(n_channel)
self.fc2 = nn.Linear(n_channel, n_output)
def reset_weights(self):
for m in self.modules():
if hasattr(m, 'reset_parameters'):
m.reset_parameters()
def forward(self, x, age, print_shape=False):
# conv-bn-relu-pool
x = self.conv1(x)
x = F.relu(self.bn1(x))
x = self.pool1(x)
x = self.conv2(x)
x = F.relu(self.bn2(x))
x = self.pool2(x)
if print_shape:
print('Shape right before squeezing:', x.shape)
x = self.final_pool(x).squeeze()
if self.use_age:
x = torch.cat((x, age.reshape(-1, 1)), dim=1)
# fc-bn-dropout-relu-fc
x = self.fc1(x)
x = self.bnfc1(x)
x = self.dropout(x)
x = F.relu(x)
x = self.fc2(x)
return x
# return F.log_softmax(x, dim=1)
model = TinyNet(n_input=train_dataset[0]['signal'].shape[0],
n_output=2,
use_age=True,
final_pool='max')
model = model.to(device, dtype=torch.float32)
print(model)
print()
# tensorboard visualization
visualize_network_tensorboard(model, 'TinyNet')
# number of parameters
n = count_parameters(model)
print(f'The Number of parameters of the model: {n:,}')
TinyNet( (conv1): Conv1d(20, 64, kernel_size=(35,), stride=(7,)) (bn1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool1): MaxPool1d(kernel_size=4, stride=4, padding=0, dilation=1, ceil_mode=False) (conv2): Conv1d(64, 64, kernel_size=(7,), stride=(1,)) (bn2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool2): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) (final_pool): AdaptiveMaxPool1d(output_size=1) (fc1): Linear(in_features=65, out_features=64, bias=True) (dropout): Dropout(p=0.3, inplace=False) (bnfc1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (fc2): Linear(in_features=64, out_features=2, bias=True) ) Shape right before squeezing: torch.Size([32, 64, 32]) The Number of parameters of the model: 78,338
record = learning_rate_search(model,
min_log_lr=-4.5,
max_log_lr=-1.4,
trials=300,
epochs=1)
draw_learning_rate_record(record)
best_log_lr = record[np.argmax(np.array([v for lr, v in record]))][0]
# best_log_lr = -1.9358023684588126
print('best_log_lr:', best_log_lr)
best_log_lr: -2.019390017755719
# reduce the learning after [lr_schedule_step] epochs by a factor of 10
n_epoch = 500
lr_schedule_step = 200
log_interval = len(train_loader) // 2
loss_history = []
train_acc_history = []
val_acc_history = []
best_val_acc = 0
model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=10 ** best_log_lr, weight_decay=0.0001)
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=lr_schedule_step, gamma=0.1)
print(f'{"*"*40} Training Starts {"*"*40}')
for epoch in tqdm(range(1, n_epoch + 1)):
print(f'{"-"*30} Epoch {epoch:03d} / {n_epoch:03d}, Learning rate: {optimizer.param_groups[-1]["lr"]:.2e} {"-"*30}')
# train
loss, train_accuracy, train_confusion = train_one_epoch(model, optimizer, log_interval)
loss_history.extend(loss)
train_acc_history.append(train_accuracy)
# validation
val_accuracy, val_confusion = check_val_accuracy(model, repeat=5)
val_acc_history.append(val_accuracy)
if best_val_acc < val_accuracy:
best_val_acc = val_accuracy
best_model_state = deepcopy(model.state_dict())
# learning rate schedule
scheduler.step()
print()
print(f'* Train accuracy / confusion: {train_accuracy:.2f}% / {train_confusion.tolist()}, ')
print(f'* Val accuracy / confusion: {val_accuracy:.2f}% / {val_confusion.tolist()}')
print()
print(f'{"*"*40} Training Ends {"*"*40}')
# draw the training loss plot
draw_loss_plot(loss_history)
draw_accuracy_history(train_acc_history, val_acc_history)
# test the last model
last_model_state = deepcopy(model.state_dict())
last_test_accuracy, last_test_confusion, last_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (last model): {last_test_accuracy:.2f}%')
print('- Confusion matrix (last model):\n', last_test_confusion)
print()
draw_confusion(last_test_confusion)
# test the best model
model.load_state_dict(best_model_state)
best_test_accuracy, best_test_confusion, best_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (best model): {best_test_accuracy:.2f}%')
print('- Confusion matrix (best model):\n', best_test_confusion)
print()
draw_confusion(best_test_confusion)
**************************************** Training Starts ****************************************
------------------------------ Epoch 001 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.668572 - Iter 028 / 029, Loss: 0.881718 * Train accuracy / confusion: 64.98% / [[168, 194], [131, 435]], * Val accuracy / confusion: 68.81% / [[147, 83], [101, 259]] ------------------------------ Epoch 002 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.526744 - Iter 028 / 029, Loss: 0.617468 * Train accuracy / confusion: 69.18% / [[184, 175], [111, 458]], * Val accuracy / confusion: 74.41% / [[113, 117], [34, 326]] ------------------------------ Epoch 003 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.472982 - Iter 028 / 029, Loss: 0.610683 * Train accuracy / confusion: 71.01% / [[190, 171], [98, 469]], * Val accuracy / confusion: 68.98% / [[50, 180], [3, 357]] ------------------------------ Epoch 004 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.671066 - Iter 028 / 029, Loss: 0.583764 * Train accuracy / confusion: 73.81% / [[226, 139], [104, 459]], * Val accuracy / confusion: 74.07% / [[132, 98], [55, 305]] ------------------------------ Epoch 005 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.633374 - Iter 028 / 029, Loss: 0.557135 * Train accuracy / confusion: 74.25% / [[221, 138], [101, 468]], * Val accuracy / confusion: 72.37% / [[149, 81], [82, 278]] ------------------------------ Epoch 006 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.507040 - Iter 028 / 029, Loss: 0.597523 * Train accuracy / confusion: 75.11% / [[220, 141], [90, 477]], * Val accuracy / confusion: 70.34% / [[183, 47], [128, 232]] ------------------------------ Epoch 007 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.618383 - Iter 028 / 029, Loss: 0.423324 * Train accuracy / confusion: 70.58% / [[207, 155], [118, 448]], * Val accuracy / confusion: 73.56% / [[103, 127], [29, 331]] ------------------------------ Epoch 008 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.710068 - Iter 028 / 029, Loss: 0.474291 * Train accuracy / confusion: 72.95% / [[201, 158], [93, 476]], * Val accuracy / confusion: 73.56% / [[137, 93], [63, 297]] ------------------------------ Epoch 009 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.409016 - Iter 028 / 029, Loss: 0.430339 * Train accuracy / confusion: 75.86% / [[229, 133], [91, 475]], * Val accuracy / confusion: 74.41% / [[140, 90], [61, 299]] ------------------------------ Epoch 010 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.426734 - Iter 028 / 029, Loss: 0.585581 * Train accuracy / confusion: 73.28% / [[218, 146], [102, 462]], * Val accuracy / confusion: 73.05% / [[121, 109], [50, 310]] ------------------------------ Epoch 011 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.446481 - Iter 028 / 029, Loss: 0.492804 * Train accuracy / confusion: 73.28% / [[214, 145], [103, 466]], * Val accuracy / confusion: 74.07% / [[155, 75], [78, 282]] ------------------------------ Epoch 012 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.574971 - Iter 028 / 029, Loss: 0.449792 * Train accuracy / confusion: 71.44% / [[188, 171], [94, 475]], * Val accuracy / confusion: 73.05% / [[100, 130], [29, 331]] ------------------------------ Epoch 013 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.468102 - Iter 028 / 029, Loss: 0.406084 * Train accuracy / confusion: 73.71% / [[229, 135], [109, 455]], * Val accuracy / confusion: 74.24% / [[145, 85], [67, 293]] ------------------------------ Epoch 014 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.436877 - Iter 028 / 029, Loss: 0.476081 * Train accuracy / confusion: 72.74% / [[190, 169], [84, 485]], * Val accuracy / confusion: 74.07% / [[137, 93], [60, 300]] ------------------------------ Epoch 015 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.520898 - Iter 028 / 029, Loss: 0.506459 * Train accuracy / confusion: 74.35% / [[214, 147], [91, 476]], * Val accuracy / confusion: 70.51% / [[83, 147], [27, 333]] ------------------------------ Epoch 016 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.761953 - Iter 028 / 029, Loss: 0.583534 * Train accuracy / confusion: 72.41% / [[206, 157], [99, 466]], * Val accuracy / confusion: 73.73% / [[151, 79], [76, 284]] ------------------------------ Epoch 017 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.528065 - Iter 028 / 029, Loss: 0.370549 * Train accuracy / confusion: 74.03% / [[216, 148], [93, 471]], * Val accuracy / confusion: 72.54% / [[123, 107], [55, 305]] ------------------------------ Epoch 018 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.391812 - Iter 028 / 029, Loss: 0.388295 * Train accuracy / confusion: 75.11% / [[226, 134], [97, 471]], * Val accuracy / confusion: 70.51% / [[77, 153], [21, 339]] ------------------------------ Epoch 019 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.502255 - Iter 028 / 029, Loss: 0.549699 * Train accuracy / confusion: 76.19% / [[210, 152], [69, 497]], * Val accuracy / confusion: 72.54% / [[137, 93], [69, 291]] ------------------------------ Epoch 020 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.467958 - Iter 028 / 029, Loss: 0.681855 * Train accuracy / confusion: 75.54% / [[219, 139], [88, 482]], * Val accuracy / confusion: 70.68% / [[112, 118], [55, 305]] ------------------------------ Epoch 021 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.531876 - Iter 028 / 029, Loss: 0.572209 * Train accuracy / confusion: 75.11% / [[200, 160], [71, 497]], * Val accuracy / confusion: 73.05% / [[97, 133], [26, 334]] ------------------------------ Epoch 022 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.604309 - Iter 028 / 029, Loss: 0.479502 * Train accuracy / confusion: 75.97% / [[236, 125], [98, 469]], * Val accuracy / confusion: 70.68% / [[123, 107], [66, 294]] ------------------------------ Epoch 023 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.574145 - Iter 028 / 029, Loss: 0.438158 * Train accuracy / confusion: 75.65% / [[236, 126], [100, 466]], * Val accuracy / confusion: 73.73% / [[147, 83], [72, 288]] ------------------------------ Epoch 024 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.537515 - Iter 028 / 029, Loss: 0.551224 * Train accuracy / confusion: 75.43% / [[212, 149], [79, 488]], * Val accuracy / confusion: 72.88% / [[138, 92], [68, 292]] ------------------------------ Epoch 025 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.551787 - Iter 028 / 029, Loss: 0.404473 * Train accuracy / confusion: 77.59% / [[236, 129], [79, 484]], * Val accuracy / confusion: 72.37% / [[147, 83], [80, 280]] ------------------------------ Epoch 026 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.520127 - Iter 028 / 029, Loss: 0.543123 * Train accuracy / confusion: 75.54% / [[221, 139], [88, 480]], * Val accuracy / confusion: 73.56% / [[123, 107], [49, 311]] ------------------------------ Epoch 027 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.466712 - Iter 028 / 029, Loss: 0.385948 * Train accuracy / confusion: 76.08% / [[222, 141], [81, 484]], * Val accuracy / confusion: 74.75% / [[154, 76], [73, 287]] ------------------------------ Epoch 028 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.573395 - Iter 028 / 029, Loss: 0.586678 * Train accuracy / confusion: 75.97% / [[229, 134], [89, 476]], * Val accuracy / confusion: 73.56% / [[101, 129], [27, 333]] ------------------------------ Epoch 029 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.362962 - Iter 028 / 029, Loss: 0.469283 * Train accuracy / confusion: 74.78% / [[222, 139], [95, 472]], * Val accuracy / confusion: 73.56% / [[114, 116], [40, 320]] ------------------------------ Epoch 030 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.620964 - Iter 028 / 029, Loss: 0.425586 * Train accuracy / confusion: 76.40% / [[211, 154], [65, 498]], * Val accuracy / confusion: 73.56% / [[155, 75], [81, 279]] ------------------------------ Epoch 031 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.472351 - Iter 028 / 029, Loss: 0.417186 * Train accuracy / confusion: 76.83% / [[226, 133], [82, 487]], * Val accuracy / confusion: 74.58% / [[147, 83], [67, 293]] ------------------------------ Epoch 032 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.530236 - Iter 028 / 029, Loss: 0.403145 * Train accuracy / confusion: 78.02% / [[243, 122], [82, 481]], * Val accuracy / confusion: 74.41% / [[140, 90], [61, 299]] ------------------------------ Epoch 033 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.438339 - Iter 028 / 029, Loss: 0.515647 * Train accuracy / confusion: 76.19% / [[232, 131], [90, 475]], * Val accuracy / confusion: 71.53% / [[125, 105], [63, 297]] ------------------------------ Epoch 034 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.613742 - Iter 028 / 029, Loss: 0.460383 * Train accuracy / confusion: 75.11% / [[222, 142], [89, 475]], * Val accuracy / confusion: 72.03% / [[125, 105], [60, 300]] ------------------------------ Epoch 035 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.468278 - Iter 028 / 029, Loss: 0.754086 * Train accuracy / confusion: 76.72% / [[235, 127], [89, 477]], * Val accuracy / confusion: 73.73% / [[148, 82], [73, 287]] ------------------------------ Epoch 036 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.688809 - Iter 028 / 029, Loss: 0.455067 * Train accuracy / confusion: 75.00% / [[212, 151], [81, 484]], * Val accuracy / confusion: 75.08% / [[119, 111], [36, 324]] ------------------------------ Epoch 037 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.520838 - Iter 028 / 029, Loss: 0.511904 * Train accuracy / confusion: 77.16% / [[227, 131], [81, 489]], * Val accuracy / confusion: 75.08% / [[146, 84], [63, 297]] ------------------------------ Epoch 038 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.439832 - Iter 028 / 029, Loss: 0.635341 * Train accuracy / confusion: 75.11% / [[212, 154], [77, 485]], * Val accuracy / confusion: 74.24% / [[159, 71], [81, 279]] ------------------------------ Epoch 039 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.450567 - Iter 028 / 029, Loss: 0.418565 * Train accuracy / confusion: 76.19% / [[218, 142], [79, 489]], * Val accuracy / confusion: 73.05% / [[116, 114], [45, 315]] ------------------------------ Epoch 040 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.678954 - Iter 028 / 029, Loss: 0.619836 * Train accuracy / confusion: 77.59% / [[228, 131], [77, 492]], * Val accuracy / confusion: 72.88% / [[135, 95], [65, 295]] ------------------------------ Epoch 041 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.376858 - Iter 028 / 029, Loss: 0.429223 * Train accuracy / confusion: 77.26% / [[238, 125], [86, 479]], * Val accuracy / confusion: 73.56% / [[153, 77], [79, 281]] ------------------------------ Epoch 042 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.503489 - Iter 028 / 029, Loss: 0.343160 * Train accuracy / confusion: 76.62% / [[238, 124], [93, 473]], * Val accuracy / confusion: 74.92% / [[128, 102], [46, 314]] ------------------------------ Epoch 043 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.496059 - Iter 028 / 029, Loss: 0.515448 * Train accuracy / confusion: 78.02% / [[227, 132], [72, 497]], * Val accuracy / confusion: 73.39% / [[147, 83], [74, 286]] ------------------------------ Epoch 044 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.873340 - Iter 028 / 029, Loss: 0.574297 * Train accuracy / confusion: 75.11% / [[220, 142], [89, 477]], * Val accuracy / confusion: 73.39% / [[119, 111], [46, 314]] ------------------------------ Epoch 045 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.425212 - Iter 028 / 029, Loss: 0.383417 * Train accuracy / confusion: 76.08% / [[230, 134], [88, 476]], * Val accuracy / confusion: 73.05% / [[103, 127], [32, 328]] ------------------------------ Epoch 046 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.455808 - Iter 028 / 029, Loss: 0.543164 * Train accuracy / confusion: 76.40% / [[219, 143], [76, 490]], * Val accuracy / confusion: 72.20% / [[141, 89], [75, 285]] ------------------------------ Epoch 047 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.451983 - Iter 028 / 029, Loss: 0.387870 * Train accuracy / confusion: 77.69% / [[245, 121], [86, 476]], * Val accuracy / confusion: 75.25% / [[124, 106], [40, 320]] ------------------------------ Epoch 048 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.545023 - Iter 028 / 029, Loss: 0.441992 * Train accuracy / confusion: 76.51% / [[223, 140], [78, 487]], * Val accuracy / confusion: 72.20% / [[135, 95], [69, 291]] ------------------------------ Epoch 049 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.561956 - Iter 028 / 029, Loss: 0.421531 * Train accuracy / confusion: 77.16% / [[234, 128], [84, 482]], * Val accuracy / confusion: 72.37% / [[132, 98], [65, 295]] ------------------------------ Epoch 050 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.473038 - Iter 028 / 029, Loss: 0.605678 * Train accuracy / confusion: 77.37% / [[239, 123], [87, 479]], * Val accuracy / confusion: 74.24% / [[107, 123], [29, 331]] ------------------------------ Epoch 051 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.501304 - Iter 028 / 029, Loss: 0.473580 * Train accuracy / confusion: 77.26% / [[215, 142], [69, 502]], * Val accuracy / confusion: 72.88% / [[141, 89], [71, 289]] ------------------------------ Epoch 052 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.369645 - Iter 028 / 029, Loss: 0.609837 * Train accuracy / confusion: 77.26% / [[228, 132], [79, 489]], * Val accuracy / confusion: 72.71% / [[137, 93], [68, 292]] ------------------------------ Epoch 053 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.335017 - Iter 028 / 029, Loss: 0.375401 * Train accuracy / confusion: 75.43% / [[216, 147], [81, 484]], * Val accuracy / confusion: 74.58% / [[140, 90], [60, 300]] ------------------------------ Epoch 054 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.667297 - Iter 028 / 029, Loss: 0.447985 * Train accuracy / confusion: 78.34% / [[231, 128], [73, 496]], * Val accuracy / confusion: 72.88% / [[125, 105], [55, 305]] ------------------------------ Epoch 055 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.416542 - Iter 028 / 029, Loss: 0.563778 * Train accuracy / confusion: 77.37% / [[232, 131], [79, 486]], * Val accuracy / confusion: 74.41% / [[134, 96], [55, 305]] ------------------------------ Epoch 056 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.507353 - Iter 028 / 029, Loss: 0.494910 * Train accuracy / confusion: 76.83% / [[221, 140], [75, 492]], * Val accuracy / confusion: 74.24% / [[136, 94], [58, 302]] ------------------------------ Epoch 057 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.342829 - Iter 028 / 029, Loss: 0.455360 * Train accuracy / confusion: 77.37% / [[224, 137], [73, 494]], * Val accuracy / confusion: 73.73% / [[115, 115], [40, 320]] ------------------------------ Epoch 058 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.447359 - Iter 028 / 029, Loss: 0.438919 * Train accuracy / confusion: 75.75% / [[220, 143], [82, 483]], * Val accuracy / confusion: 76.78% / [[147, 83], [54, 306]] ------------------------------ Epoch 059 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.487179 - Iter 028 / 029, Loss: 0.399704 * Train accuracy / confusion: 78.12% / [[241, 122], [81, 484]], * Val accuracy / confusion: 72.71% / [[173, 57], [104, 256]] ------------------------------ Epoch 060 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.589891 - Iter 028 / 029, Loss: 0.369608 * Train accuracy / confusion: 77.59% / [[227, 137], [71, 493]], * Val accuracy / confusion: 72.88% / [[96, 134], [26, 334]] ------------------------------ Epoch 061 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.557061 - Iter 028 / 029, Loss: 0.612388 * Train accuracy / confusion: 78.88% / [[237, 121], [75, 495]], * Val accuracy / confusion: 73.05% / [[138, 92], [67, 293]] ------------------------------ Epoch 062 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.432142 - Iter 028 / 029, Loss: 0.571337 * Train accuracy / confusion: 76.83% / [[225, 134], [81, 488]], * Val accuracy / confusion: 71.53% / [[173, 57], [111, 249]] ------------------------------ Epoch 063 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.597579 - Iter 028 / 029, Loss: 0.752412 * Train accuracy / confusion: 78.99% / [[237, 127], [68, 496]], * Val accuracy / confusion: 73.39% / [[131, 99], [58, 302]] ------------------------------ Epoch 064 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.531925 - Iter 028 / 029, Loss: 0.414573 * Train accuracy / confusion: 79.20% / [[248, 115], [78, 487]], * Val accuracy / confusion: 72.20% / [[138, 92], [72, 288]] ------------------------------ Epoch 065 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.639599 - Iter 028 / 029, Loss: 0.423873 * Train accuracy / confusion: 78.12% / [[233, 127], [76, 492]], * Val accuracy / confusion: 73.56% / [[141, 89], [67, 293]] ------------------------------ Epoch 066 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.509683 - Iter 028 / 029, Loss: 0.520998 * Train accuracy / confusion: 76.40% / [[216, 144], [75, 493]], * Val accuracy / confusion: 75.59% / [[134, 96], [48, 312]] ------------------------------ Epoch 067 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.487896 - Iter 028 / 029, Loss: 0.576633 * Train accuracy / confusion: 76.51% / [[231, 133], [85, 479]], * Val accuracy / confusion: 70.68% / [[95, 135], [38, 322]] ------------------------------ Epoch 068 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.539319 - Iter 028 / 029, Loss: 0.493818 * Train accuracy / confusion: 78.77% / [[246, 115], [82, 485]], * Val accuracy / confusion: 72.88% / [[129, 101], [59, 301]] ------------------------------ Epoch 069 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.525087 - Iter 028 / 029, Loss: 0.493206 * Train accuracy / confusion: 77.26% / [[226, 135], [76, 491]], * Val accuracy / confusion: 73.56% / [[161, 69], [87, 273]] ------------------------------ Epoch 070 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.456662 - Iter 028 / 029, Loss: 0.503828 * Train accuracy / confusion: 76.19% / [[216, 145], [76, 491]], * Val accuracy / confusion: 75.59% / [[126, 104], [40, 320]] ------------------------------ Epoch 071 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.484894 - Iter 028 / 029, Loss: 0.522164 * Train accuracy / confusion: 77.37% / [[242, 120], [90, 476]], * Val accuracy / confusion: 73.05% / [[144, 86], [73, 287]] ------------------------------ Epoch 072 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.392491 - Iter 028 / 029, Loss: 0.372010 * Train accuracy / confusion: 79.09% / [[237, 122], [72, 497]], * Val accuracy / confusion: 74.07% / [[131, 99], [54, 306]] ------------------------------ Epoch 073 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.475420 - Iter 028 / 029, Loss: 0.713606 * Train accuracy / confusion: 78.45% / [[245, 116], [84, 483]], * Val accuracy / confusion: 73.39% / [[109, 121], [36, 324]] ------------------------------ Epoch 074 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.465055 - Iter 028 / 029, Loss: 0.613222 * Train accuracy / confusion: 76.19% / [[210, 152], [69, 497]], * Val accuracy / confusion: 72.88% / [[137, 93], [67, 293]] ------------------------------ Epoch 075 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.426370 - Iter 028 / 029, Loss: 0.379520 * Train accuracy / confusion: 76.72% / [[233, 133], [83, 479]], * Val accuracy / confusion: 73.39% / [[157, 73], [84, 276]] ------------------------------ Epoch 076 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.452641 - Iter 028 / 029, Loss: 0.350981 * Train accuracy / confusion: 79.09% / [[245, 117], [77, 489]], * Val accuracy / confusion: 74.24% / [[125, 105], [47, 313]] ------------------------------ Epoch 077 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.464150 - Iter 028 / 029, Loss: 0.633700 * Train accuracy / confusion: 76.94% / [[234, 129], [85, 480]], * Val accuracy / confusion: 71.19% / [[142, 88], [82, 278]] ------------------------------ Epoch 078 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.393666 - Iter 028 / 029, Loss: 0.527371 * Train accuracy / confusion: 77.48% / [[231, 131], [78, 488]], * Val accuracy / confusion: 71.69% / [[138, 92], [75, 285]] ------------------------------ Epoch 079 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.357352 - Iter 028 / 029, Loss: 0.437051 * Train accuracy / confusion: 77.91% / [[239, 121], [84, 484]], * Val accuracy / confusion: 74.07% / [[127, 103], [50, 310]] ------------------------------ Epoch 080 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.515849 - Iter 028 / 029, Loss: 0.414050 * Train accuracy / confusion: 78.56% / [[237, 130], [69, 492]], * Val accuracy / confusion: 74.58% / [[157, 73], [77, 283]] ------------------------------ Epoch 081 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.498219 - Iter 028 / 029, Loss: 0.528496 * Train accuracy / confusion: 78.56% / [[249, 115], [84, 480]], * Val accuracy / confusion: 73.56% / [[124, 106], [50, 310]] ------------------------------ Epoch 082 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.498235 - Iter 028 / 029, Loss: 0.548501 * Train accuracy / confusion: 77.37% / [[234, 126], [84, 484]], * Val accuracy / confusion: 75.42% / [[169, 61], [84, 276]] ------------------------------ Epoch 083 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.541856 - Iter 028 / 029, Loss: 0.502968 * Train accuracy / confusion: 79.42% / [[244, 116], [75, 493]], * Val accuracy / confusion: 72.71% / [[117, 113], [48, 312]] ------------------------------ Epoch 084 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.263830 - Iter 028 / 029, Loss: 0.479784 * Train accuracy / confusion: 76.19% / [[228, 132], [89, 479]], * Val accuracy / confusion: 72.54% / [[136, 94], [68, 292]] ------------------------------ Epoch 085 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.386693 - Iter 028 / 029, Loss: 0.496347 * Train accuracy / confusion: 76.19% / [[221, 140], [81, 486]], * Val accuracy / confusion: 72.88% / [[121, 109], [51, 309]] ------------------------------ Epoch 086 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.407095 - Iter 028 / 029, Loss: 0.519997 * Train accuracy / confusion: 78.34% / [[236, 127], [74, 491]], * Val accuracy / confusion: 75.59% / [[133, 97], [47, 313]] ------------------------------ Epoch 087 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.408336 - Iter 028 / 029, Loss: 0.529187 * Train accuracy / confusion: 78.12% / [[247, 115], [88, 478]], * Val accuracy / confusion: 74.07% / [[143, 87], [66, 294]] ------------------------------ Epoch 088 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.410092 - Iter 028 / 029, Loss: 0.361518 * Train accuracy / confusion: 78.77% / [[243, 117], [80, 488]], * Val accuracy / confusion: 71.86% / [[128, 102], [64, 296]] ------------------------------ Epoch 089 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.451775 - Iter 028 / 029, Loss: 0.328745 * Train accuracy / confusion: 77.69% / [[230, 130], [77, 491]], * Val accuracy / confusion: 72.03% / [[122, 108], [57, 303]] ------------------------------ Epoch 090 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.539925 - Iter 028 / 029, Loss: 0.449726 * Train accuracy / confusion: 78.12% / [[246, 119], [84, 479]], * Val accuracy / confusion: 74.07% / [[145, 85], [68, 292]] ------------------------------ Epoch 091 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.626008 - Iter 028 / 029, Loss: 0.472265 * Train accuracy / confusion: 78.66% / [[233, 126], [72, 497]], * Val accuracy / confusion: 74.24% / [[131, 99], [53, 307]] ------------------------------ Epoch 092 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.490250 - Iter 028 / 029, Loss: 0.380773 * Train accuracy / confusion: 77.05% / [[235, 128], [85, 480]], * Val accuracy / confusion: 73.90% / [[127, 103], [51, 309]] ------------------------------ Epoch 093 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.519861 - Iter 028 / 029, Loss: 0.399489 * Train accuracy / confusion: 79.63% / [[246, 116], [73, 493]], * Val accuracy / confusion: 68.31% / [[115, 115], [72, 288]] ------------------------------ Epoch 094 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.535558 - Iter 028 / 029, Loss: 0.481188 * Train accuracy / confusion: 79.96% / [[248, 116], [70, 494]], * Val accuracy / confusion: 70.34% / [[156, 74], [101, 259]] ------------------------------ Epoch 095 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.503343 - Iter 028 / 029, Loss: 0.422627 * Train accuracy / confusion: 78.99% / [[235, 126], [69, 498]], * Val accuracy / confusion: 70.17% / [[173, 57], [119, 241]] ------------------------------ Epoch 096 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.553458 - Iter 028 / 029, Loss: 0.434368 * Train accuracy / confusion: 77.69% / [[243, 120], [87, 478]], * Val accuracy / confusion: 74.58% / [[178, 52], [98, 262]] ------------------------------ Epoch 097 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.540780 - Iter 028 / 029, Loss: 0.384766 * Train accuracy / confusion: 76.62% / [[231, 124], [93, 480]], * Val accuracy / confusion: 72.88% / [[116, 114], [46, 314]] ------------------------------ Epoch 098 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.614931 - Iter 028 / 029, Loss: 0.451019 * Train accuracy / confusion: 77.80% / [[230, 131], [75, 492]], * Val accuracy / confusion: 74.58% / [[134, 96], [54, 306]] ------------------------------ Epoch 099 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.458141 - Iter 028 / 029, Loss: 0.557460 * Train accuracy / confusion: 78.45% / [[242, 121], [79, 486]], * Val accuracy / confusion: 75.42% / [[146, 84], [61, 299]] ------------------------------ Epoch 100 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.515131 - Iter 028 / 029, Loss: 0.410509 * Train accuracy / confusion: 79.20% / [[239, 123], [70, 496]], * Val accuracy / confusion: 75.25% / [[146, 84], [62, 298]] ------------------------------ Epoch 101 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.658817 - Iter 028 / 029, Loss: 0.430686 * Train accuracy / confusion: 78.99% / [[237, 122], [73, 496]], * Val accuracy / confusion: 75.59% / [[144, 86], [58, 302]] ------------------------------ Epoch 102 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.358905 - Iter 028 / 029, Loss: 0.380119 * Train accuracy / confusion: 76.94% / [[225, 137], [77, 489]], * Val accuracy / confusion: 72.88% / [[101, 129], [31, 329]] ------------------------------ Epoch 103 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.563392 - Iter 028 / 029, Loss: 0.375598 * Train accuracy / confusion: 76.62% / [[232, 130], [87, 479]], * Val accuracy / confusion: 75.59% / [[148, 82], [62, 298]] ------------------------------ Epoch 104 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.463252 - Iter 028 / 029, Loss: 0.490775 * Train accuracy / confusion: 77.91% / [[236, 125], [80, 487]], * Val accuracy / confusion: 74.41% / [[145, 85], [66, 294]] ------------------------------ Epoch 105 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.407403 - Iter 028 / 029, Loss: 0.483304 * Train accuracy / confusion: 78.66% / [[244, 120], [78, 486]], * Val accuracy / confusion: 72.54% / [[141, 89], [73, 287]] ------------------------------ Epoch 106 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.425269 - Iter 028 / 029, Loss: 0.465290 * Train accuracy / confusion: 78.34% / [[242, 122], [79, 485]], * Val accuracy / confusion: 75.25% / [[142, 88], [58, 302]] ------------------------------ Epoch 107 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.363668 - Iter 028 / 029, Loss: 0.359940 * Train accuracy / confusion: 78.12% / [[232, 129], [74, 493]], * Val accuracy / confusion: 74.58% / [[162, 68], [82, 278]] ------------------------------ Epoch 108 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.412587 - Iter 028 / 029, Loss: 0.350866 * Train accuracy / confusion: 80.50% / [[248, 113], [68, 499]], * Val accuracy / confusion: 74.24% / [[144, 86], [66, 294]] ------------------------------ Epoch 109 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.448561 - Iter 028 / 029, Loss: 0.481127 * Train accuracy / confusion: 77.91% / [[235, 125], [80, 488]], * Val accuracy / confusion: 74.07% / [[131, 99], [54, 306]] ------------------------------ Epoch 110 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.713030 - Iter 028 / 029, Loss: 0.427297 * Train accuracy / confusion: 78.12% / [[224, 135], [68, 501]], * Val accuracy / confusion: 72.20% / [[149, 81], [83, 277]] ------------------------------ Epoch 111 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.533735 - Iter 028 / 029, Loss: 0.456320 * Train accuracy / confusion: 79.63% / [[248, 113], [76, 491]], * Val accuracy / confusion: 75.59% / [[155, 75], [69, 291]] ------------------------------ Epoch 112 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.568775 - Iter 028 / 029, Loss: 0.420789 * Train accuracy / confusion: 77.37% / [[230, 130], [80, 488]], * Val accuracy / confusion: 72.54% / [[104, 126], [36, 324]] ------------------------------ Epoch 113 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.306609 - Iter 028 / 029, Loss: 0.484168 * Train accuracy / confusion: 79.74% / [[247, 113], [75, 493]], * Val accuracy / confusion: 73.73% / [[109, 121], [34, 326]] ------------------------------ Epoch 114 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.339476 - Iter 028 / 029, Loss: 0.375661 * Train accuracy / confusion: 78.56% / [[241, 120], [79, 488]], * Val accuracy / confusion: 72.88% / [[168, 62], [98, 262]] ------------------------------ Epoch 115 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.353813 - Iter 028 / 029, Loss: 0.566926 * Train accuracy / confusion: 78.34% / [[247, 114], [87, 480]], * Val accuracy / confusion: 74.24% / [[139, 91], [61, 299]] ------------------------------ Epoch 116 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.463101 - Iter 028 / 029, Loss: 0.436131 * Train accuracy / confusion: 78.34% / [[234, 127], [74, 493]], * Val accuracy / confusion: 75.25% / [[153, 77], [69, 291]] ------------------------------ Epoch 117 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.444261 - Iter 028 / 029, Loss: 0.363365 * Train accuracy / confusion: 78.56% / [[232, 130], [69, 497]], * Val accuracy / confusion: 74.07% / [[118, 112], [41, 319]] ------------------------------ Epoch 118 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.719660 - Iter 028 / 029, Loss: 0.340411 * Train accuracy / confusion: 78.66% / [[245, 116], [82, 485]], * Val accuracy / confusion: 75.93% / [[143, 87], [55, 305]] ------------------------------ Epoch 119 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.516290 - Iter 028 / 029, Loss: 0.432859 * Train accuracy / confusion: 80.06% / [[265, 96], [89, 478]], * Val accuracy / confusion: 72.37% / [[104, 126], [37, 323]] ------------------------------ Epoch 120 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.330930 - Iter 028 / 029, Loss: 0.382130 * Train accuracy / confusion: 77.05% / [[223, 140], [73, 492]], * Val accuracy / confusion: 71.19% / [[176, 54], [116, 244]] ------------------------------ Epoch 121 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.397200 - Iter 028 / 029, Loss: 0.410711 * Train accuracy / confusion: 79.96% / [[245, 114], [72, 497]], * Val accuracy / confusion: 74.41% / [[140, 90], [61, 299]] ------------------------------ Epoch 122 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.569450 - Iter 028 / 029, Loss: 0.420696 * Train accuracy / confusion: 79.53% / [[256, 108], [82, 482]], * Val accuracy / confusion: 75.42% / [[145, 85], [60, 300]] ------------------------------ Epoch 123 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.425715 - Iter 028 / 029, Loss: 0.368285 * Train accuracy / confusion: 78.12% / [[245, 111], [92, 480]], * Val accuracy / confusion: 74.58% / [[140, 90], [60, 300]] ------------------------------ Epoch 124 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.493185 - Iter 028 / 029, Loss: 0.409758 * Train accuracy / confusion: 78.45% / [[246, 116], [84, 482]], * Val accuracy / confusion: 73.22% / [[151, 79], [79, 281]] ------------------------------ Epoch 125 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.445793 - Iter 028 / 029, Loss: 0.337245 * Train accuracy / confusion: 79.53% / [[249, 114], [76, 489]], * Val accuracy / confusion: 71.19% / [[98, 132], [38, 322]] ------------------------------ Epoch 126 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.345856 - Iter 028 / 029, Loss: 0.275453 * Train accuracy / confusion: 81.03% / [[253, 106], [70, 499]], * Val accuracy / confusion: 73.05% / [[134, 96], [63, 297]] ------------------------------ Epoch 127 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.554959 - Iter 028 / 029, Loss: 0.493006 * Train accuracy / confusion: 79.09% / [[245, 117], [77, 489]], * Val accuracy / confusion: 72.88% / [[116, 114], [46, 314]] ------------------------------ Epoch 128 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.494626 - Iter 028 / 029, Loss: 0.386622 * Train accuracy / confusion: 78.66% / [[245, 115], [83, 485]], * Val accuracy / confusion: 71.36% / [[140, 90], [79, 281]] ------------------------------ Epoch 129 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.326060 - Iter 028 / 029, Loss: 0.586922 * Train accuracy / confusion: 79.09% / [[236, 125], [69, 498]], * Val accuracy / confusion: 71.19% / [[91, 139], [31, 329]] ------------------------------ Epoch 130 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.478656 - Iter 028 / 029, Loss: 0.398380 * Train accuracy / confusion: 78.99% / [[242, 119], [76, 491]], * Val accuracy / confusion: 72.37% / [[141, 89], [74, 286]] ------------------------------ Epoch 131 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.538438 - Iter 028 / 029, Loss: 0.486351 * Train accuracy / confusion: 78.02% / [[246, 115], [89, 478]], * Val accuracy / confusion: 71.36% / [[111, 119], [50, 310]] ------------------------------ Epoch 132 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.419615 - Iter 028 / 029, Loss: 0.341354 * Train accuracy / confusion: 79.42% / [[246, 116], [75, 491]], * Val accuracy / confusion: 72.20% / [[121, 109], [55, 305]] ------------------------------ Epoch 133 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.407200 - Iter 028 / 029, Loss: 0.361882 * Train accuracy / confusion: 79.74% / [[252, 115], [73, 488]], * Val accuracy / confusion: 74.24% / [[171, 59], [93, 267]] ------------------------------ Epoch 134 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.489830 - Iter 028 / 029, Loss: 0.377496 * Train accuracy / confusion: 81.03% / [[258, 104], [72, 494]], * Val accuracy / confusion: 73.90% / [[135, 95], [59, 301]] ------------------------------ Epoch 135 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.570949 - Iter 028 / 029, Loss: 0.658696 * Train accuracy / confusion: 78.99% / [[246, 116], [79, 487]], * Val accuracy / confusion: 75.59% / [[154, 76], [68, 292]] ------------------------------ Epoch 136 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.354847 - Iter 028 / 029, Loss: 0.664944 * Train accuracy / confusion: 79.74% / [[232, 131], [57, 508]], * Val accuracy / confusion: 74.41% / [[138, 92], [59, 301]] ------------------------------ Epoch 137 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.418639 - Iter 028 / 029, Loss: 0.392377 * Train accuracy / confusion: 78.02% / [[242, 121], [83, 482]], * Val accuracy / confusion: 74.07% / [[112, 118], [35, 325]] ------------------------------ Epoch 138 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.465493 - Iter 028 / 029, Loss: 0.339955 * Train accuracy / confusion: 79.20% / [[247, 114], [79, 488]], * Val accuracy / confusion: 69.83% / [[176, 54], [124, 236]] ------------------------------ Epoch 139 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.447959 - Iter 028 / 029, Loss: 0.535925 * Train accuracy / confusion: 79.74% / [[242, 119], [69, 498]], * Val accuracy / confusion: 73.22% / [[117, 113], [45, 315]] ------------------------------ Epoch 140 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.455909 - Iter 028 / 029, Loss: 0.394782 * Train accuracy / confusion: 80.28% / [[246, 116], [67, 499]], * Val accuracy / confusion: 72.88% / [[115, 115], [45, 315]] ------------------------------ Epoch 141 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.413096 - Iter 028 / 029, Loss: 0.383803 * Train accuracy / confusion: 80.28% / [[253, 108], [75, 492]], * Val accuracy / confusion: 74.07% / [[130, 100], [53, 307]] ------------------------------ Epoch 142 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.434893 - Iter 028 / 029, Loss: 0.328520 * Train accuracy / confusion: 78.12% / [[242, 118], [85, 483]], * Val accuracy / confusion: 71.86% / [[147, 83], [83, 277]] ------------------------------ Epoch 143 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.439000 - Iter 028 / 029, Loss: 0.544679 * Train accuracy / confusion: 80.82% / [[246, 116], [62, 504]], * Val accuracy / confusion: 73.56% / [[136, 94], [62, 298]] ------------------------------ Epoch 144 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.481555 - Iter 028 / 029, Loss: 0.341664 * Train accuracy / confusion: 80.82% / [[251, 110], [68, 499]], * Val accuracy / confusion: 73.39% / [[129, 101], [56, 304]] ------------------------------ Epoch 145 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.312292 - Iter 028 / 029, Loss: 0.385089 * Train accuracy / confusion: 78.12% / [[241, 119], [84, 484]], * Val accuracy / confusion: 74.58% / [[134, 96], [54, 306]] ------------------------------ Epoch 146 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.469782 - Iter 028 / 029, Loss: 0.367519 * Train accuracy / confusion: 78.23% / [[232, 128], [74, 494]], * Val accuracy / confusion: 76.78% / [[142, 88], [49, 311]] ------------------------------ Epoch 147 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.400958 - Iter 028 / 029, Loss: 0.535911 * Train accuracy / confusion: 80.39% / [[244, 114], [68, 502]], * Val accuracy / confusion: 74.75% / [[162, 68], [81, 279]] ------------------------------ Epoch 148 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.711765 - Iter 028 / 029, Loss: 0.647820 * Train accuracy / confusion: 79.74% / [[235, 125], [63, 505]], * Val accuracy / confusion: 74.24% / [[147, 83], [69, 291]] ------------------------------ Epoch 149 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.427977 - Iter 028 / 029, Loss: 0.456188 * Train accuracy / confusion: 80.82% / [[253, 106], [72, 497]], * Val accuracy / confusion: 74.58% / [[148, 82], [68, 292]] ------------------------------ Epoch 150 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.271937 - Iter 028 / 029, Loss: 0.256495 * Train accuracy / confusion: 78.56% / [[236, 125], [74, 493]], * Val accuracy / confusion: 73.56% / [[118, 112], [44, 316]] ------------------------------ Epoch 151 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.508135 - Iter 028 / 029, Loss: 0.689274 * Train accuracy / confusion: 79.53% / [[235, 125], [65, 503]], * Val accuracy / confusion: 76.10% / [[135, 95], [46, 314]] ------------------------------ Epoch 152 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.368208 - Iter 028 / 029, Loss: 0.270714 * Train accuracy / confusion: 79.63% / [[247, 118], [71, 492]], * Val accuracy / confusion: 71.53% / [[137, 93], [75, 285]] ------------------------------ Epoch 153 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.390404 - Iter 028 / 029, Loss: 0.435954 * Train accuracy / confusion: 79.74% / [[258, 107], [81, 482]], * Val accuracy / confusion: 74.41% / [[141, 89], [62, 298]] ------------------------------ Epoch 154 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.646313 - Iter 028 / 029, Loss: 0.372599 * Train accuracy / confusion: 79.31% / [[239, 127], [65, 497]], * Val accuracy / confusion: 74.58% / [[157, 73], [77, 283]] ------------------------------ Epoch 155 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.519071 - Iter 028 / 029, Loss: 0.447726 * Train accuracy / confusion: 81.57% / [[264, 100], [71, 493]], * Val accuracy / confusion: 74.41% / [[138, 92], [59, 301]] ------------------------------ Epoch 156 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.380033 - Iter 028 / 029, Loss: 0.468195 * Train accuracy / confusion: 78.99% / [[258, 104], [91, 475]], * Val accuracy / confusion: 74.92% / [[133, 97], [51, 309]] ------------------------------ Epoch 157 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.470401 - Iter 028 / 029, Loss: 0.452537 * Train accuracy / confusion: 81.03% / [[244, 116], [60, 508]], * Val accuracy / confusion: 73.39% / [[127, 103], [54, 306]] ------------------------------ Epoch 158 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.651418 - Iter 028 / 029, Loss: 0.462084 * Train accuracy / confusion: 79.96% / [[248, 116], [70, 494]], * Val accuracy / confusion: 73.73% / [[155, 75], [80, 280]] ------------------------------ Epoch 159 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.464037 - Iter 028 / 029, Loss: 0.447595 * Train accuracy / confusion: 80.06% / [[250, 113], [72, 493]], * Val accuracy / confusion: 76.44% / [[145, 85], [54, 306]] ------------------------------ Epoch 160 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.511286 - Iter 028 / 029, Loss: 0.360596 * Train accuracy / confusion: 78.77% / [[225, 136], [61, 506]], * Val accuracy / confusion: 73.05% / [[124, 106], [53, 307]] ------------------------------ Epoch 161 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.577232 - Iter 028 / 029, Loss: 0.458710 * Train accuracy / confusion: 77.91% / [[242, 118], [87, 481]], * Val accuracy / confusion: 73.90% / [[138, 92], [62, 298]] ------------------------------ Epoch 162 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.476723 - Iter 028 / 029, Loss: 0.339420 * Train accuracy / confusion: 79.09% / [[235, 127], [67, 499]], * Val accuracy / confusion: 73.90% / [[175, 55], [99, 261]] ------------------------------ Epoch 163 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.495040 - Iter 028 / 029, Loss: 0.431206 * Train accuracy / confusion: 80.39% / [[245, 112], [70, 501]], * Val accuracy / confusion: 74.92% / [[134, 96], [52, 308]] ------------------------------ Epoch 164 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.530951 - Iter 028 / 029, Loss: 0.318379 * Train accuracy / confusion: 79.85% / [[252, 113], [74, 489]], * Val accuracy / confusion: 72.54% / [[136, 94], [68, 292]] ------------------------------ Epoch 165 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.316474 - Iter 028 / 029, Loss: 0.485134 * Train accuracy / confusion: 79.53% / [[243, 114], [76, 495]], * Val accuracy / confusion: 73.90% / [[133, 97], [57, 303]] ------------------------------ Epoch 166 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.528662 - Iter 028 / 029, Loss: 0.455934 * Train accuracy / confusion: 79.63% / [[249, 112], [77, 490]], * Val accuracy / confusion: 72.88% / [[147, 83], [77, 283]] ------------------------------ Epoch 167 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.499491 - Iter 028 / 029, Loss: 0.475660 * Train accuracy / confusion: 80.06% / [[247, 117], [68, 496]], * Val accuracy / confusion: 73.56% / [[124, 106], [50, 310]] ------------------------------ Epoch 168 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.345580 - Iter 028 / 029, Loss: 0.448700 * Train accuracy / confusion: 80.71% / [[236, 124], [55, 513]], * Val accuracy / confusion: 72.71% / [[158, 72], [89, 271]] ------------------------------ Epoch 169 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.650221 - Iter 028 / 029, Loss: 0.598771 * Train accuracy / confusion: 79.20% / [[261, 102], [91, 474]], * Val accuracy / confusion: 72.03% / [[104, 126], [39, 321]] ------------------------------ Epoch 170 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.344603 - Iter 028 / 029, Loss: 0.367838 * Train accuracy / confusion: 79.31% / [[233, 126], [66, 503]], * Val accuracy / confusion: 73.90% / [[159, 71], [83, 277]] ------------------------------ Epoch 171 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.398215 - Iter 028 / 029, Loss: 0.435898 * Train accuracy / confusion: 79.74% / [[244, 118], [70, 496]], * Val accuracy / confusion: 73.39% / [[120, 110], [47, 313]] ------------------------------ Epoch 172 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.630255 - Iter 028 / 029, Loss: 0.431778 * Train accuracy / confusion: 80.39% / [[258, 101], [81, 488]], * Val accuracy / confusion: 72.88% / [[134, 96], [64, 296]] ------------------------------ Epoch 173 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.377812 - Iter 028 / 029, Loss: 0.459508 * Train accuracy / confusion: 82.44% / [[258, 100], [63, 507]], * Val accuracy / confusion: 72.88% / [[144, 86], [74, 286]] ------------------------------ Epoch 174 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.401807 - Iter 028 / 029, Loss: 0.762581 * Train accuracy / confusion: 80.06% / [[245, 112], [73, 498]], * Val accuracy / confusion: 74.41% / [[135, 95], [56, 304]] ------------------------------ Epoch 175 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.534364 - Iter 028 / 029, Loss: 0.487593 * Train accuracy / confusion: 78.66% / [[231, 131], [67, 499]], * Val accuracy / confusion: 71.69% / [[134, 96], [71, 289]] ------------------------------ Epoch 176 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.357815 - Iter 028 / 029, Loss: 0.557465 * Train accuracy / confusion: 79.20% / [[248, 111], [82, 487]], * Val accuracy / confusion: 74.41% / [[143, 87], [64, 296]] ------------------------------ Epoch 177 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.384948 - Iter 028 / 029, Loss: 0.502165 * Train accuracy / confusion: 79.74% / [[253, 113], [75, 487]], * Val accuracy / confusion: 73.73% / [[139, 91], [64, 296]] ------------------------------ Epoch 178 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.446897 - Iter 028 / 029, Loss: 0.437582 * Train accuracy / confusion: 79.42% / [[246, 117], [74, 491]], * Val accuracy / confusion: 71.86% / [[124, 106], [60, 300]] ------------------------------ Epoch 179 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.543410 - Iter 028 / 029, Loss: 0.465722 * Train accuracy / confusion: 77.48% / [[240, 123], [86, 479]], * Val accuracy / confusion: 72.20% / [[150, 80], [84, 276]] ------------------------------ Epoch 180 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.373500 - Iter 028 / 029, Loss: 0.370872 * Train accuracy / confusion: 81.36% / [[245, 116], [57, 510]], * Val accuracy / confusion: 72.71% / [[134, 96], [65, 295]] ------------------------------ Epoch 181 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.410187 - Iter 028 / 029, Loss: 0.475594 * Train accuracy / confusion: 80.06% / [[250, 105], [80, 493]], * Val accuracy / confusion: 74.24% / [[138, 92], [60, 300]] ------------------------------ Epoch 182 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.548252 - Iter 028 / 029, Loss: 0.321008 * Train accuracy / confusion: 79.85% / [[243, 119], [68, 498]], * Val accuracy / confusion: 72.54% / [[140, 90], [72, 288]] ------------------------------ Epoch 183 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.373194 - Iter 028 / 029, Loss: 0.494078 * Train accuracy / confusion: 79.09% / [[243, 117], [77, 491]], * Val accuracy / confusion: 74.24% / [[130, 100], [52, 308]] ------------------------------ Epoch 184 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.409536 - Iter 028 / 029, Loss: 0.476097 * Train accuracy / confusion: 80.39% / [[249, 112], [70, 497]], * Val accuracy / confusion: 75.08% / [[142, 88], [59, 301]] ------------------------------ Epoch 185 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.284210 - Iter 028 / 029, Loss: 0.445181 * Train accuracy / confusion: 80.82% / [[257, 106], [72, 493]], * Val accuracy / confusion: 72.88% / [[103, 127], [33, 327]] ------------------------------ Epoch 186 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.280687 - Iter 028 / 029, Loss: 0.465892 * Train accuracy / confusion: 78.88% / [[246, 115], [81, 486]], * Val accuracy / confusion: 74.24% / [[148, 82], [70, 290]] ------------------------------ Epoch 187 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.411422 - Iter 028 / 029, Loss: 0.422401 * Train accuracy / confusion: 80.60% / [[247, 113], [67, 501]], * Val accuracy / confusion: 75.42% / [[142, 88], [57, 303]] ------------------------------ Epoch 188 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.419790 - Iter 028 / 029, Loss: 0.549909 * Train accuracy / confusion: 80.06% / [[253, 110], [75, 490]], * Val accuracy / confusion: 74.07% / [[163, 67], [86, 274]] ------------------------------ Epoch 189 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.594233 - Iter 028 / 029, Loss: 0.417560 * Train accuracy / confusion: 79.63% / [[256, 107], [82, 483]], * Val accuracy / confusion: 71.53% / [[154, 76], [92, 268]] ------------------------------ Epoch 190 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.395942 - Iter 028 / 029, Loss: 0.412950 * Train accuracy / confusion: 80.39% / [[248, 117], [65, 498]], * Val accuracy / confusion: 72.20% / [[134, 96], [68, 292]] ------------------------------ Epoch 191 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.393183 - Iter 028 / 029, Loss: 0.394843 * Train accuracy / confusion: 79.74% / [[259, 103], [85, 481]], * Val accuracy / confusion: 73.05% / [[124, 106], [53, 307]] ------------------------------ Epoch 192 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.554670 - Iter 028 / 029, Loss: 0.392585 * Train accuracy / confusion: 79.31% / [[248, 116], [76, 488]], * Val accuracy / confusion: 73.22% / [[146, 84], [74, 286]] ------------------------------ Epoch 193 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.445041 - Iter 028 / 029, Loss: 0.434397 * Train accuracy / confusion: 80.93% / [[246, 116], [61, 505]], * Val accuracy / confusion: 73.39% / [[144, 86], [71, 289]] ------------------------------ Epoch 194 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.344751 - Iter 028 / 029, Loss: 0.591220 * Train accuracy / confusion: 78.99% / [[255, 109], [86, 478]], * Val accuracy / confusion: 77.12% / [[152, 78], [57, 303]] ------------------------------ Epoch 195 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.369714 - Iter 028 / 029, Loss: 0.266511 * Train accuracy / confusion: 81.14% / [[262, 100], [75, 491]], * Val accuracy / confusion: 74.41% / [[151, 79], [72, 288]] ------------------------------ Epoch 196 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.377592 - Iter 028 / 029, Loss: 0.585019 * Train accuracy / confusion: 80.71% / [[249, 114], [65, 500]], * Val accuracy / confusion: 73.05% / [[113, 117], [42, 318]] ------------------------------ Epoch 197 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.480226 - Iter 028 / 029, Loss: 0.394766 * Train accuracy / confusion: 79.74% / [[247, 115], [73, 493]], * Val accuracy / confusion: 72.88% / [[124, 106], [54, 306]] ------------------------------ Epoch 198 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.509333 - Iter 028 / 029, Loss: 0.358007 * Train accuracy / confusion: 80.71% / [[249, 107], [72, 500]], * Val accuracy / confusion: 74.07% / [[128, 102], [51, 309]] ------------------------------ Epoch 199 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.346694 - Iter 028 / 029, Loss: 0.469336 * Train accuracy / confusion: 79.31% / [[239, 124], [68, 497]], * Val accuracy / confusion: 74.07% / [[157, 73], [80, 280]] ------------------------------ Epoch 200 / 500, Learning rate: 9.56e-03 ------------------------------ - Iter 014 / 029, Loss: 0.323045 - Iter 028 / 029, Loss: 0.412533 * Train accuracy / confusion: 79.96% / [[258, 105], [81, 484]], * Val accuracy / confusion: 74.07% / [[107, 123], [30, 330]] ------------------------------ Epoch 201 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.351169 - Iter 028 / 029, Loss: 0.568605 * Train accuracy / confusion: 81.57% / [[243, 122], [49, 514]], * Val accuracy / confusion: 73.39% / [[128, 102], [55, 305]] ------------------------------ Epoch 202 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.421129 - Iter 028 / 029, Loss: 0.316624 * Train accuracy / confusion: 78.99% / [[237, 124], [71, 496]], * Val accuracy / confusion: 73.56% / [[133, 97], [59, 301]] ------------------------------ Epoch 203 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.632228 - Iter 028 / 029, Loss: 0.375607 * Train accuracy / confusion: 79.96% / [[242, 119], [67, 500]], * Val accuracy / confusion: 74.24% / [[135, 95], [57, 303]] ------------------------------ Epoch 204 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.308610 - Iter 028 / 029, Loss: 0.697931 * Train accuracy / confusion: 79.09% / [[243, 121], [73, 491]], * Val accuracy / confusion: 73.39% / [[134, 96], [61, 299]] ------------------------------ Epoch 205 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.402721 - Iter 028 / 029, Loss: 0.479184 * Train accuracy / confusion: 79.20% / [[242, 117], [76, 493]], * Val accuracy / confusion: 75.08% / [[146, 84], [63, 297]] ------------------------------ Epoch 206 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.277777 - Iter 028 / 029, Loss: 0.430633 * Train accuracy / confusion: 80.50% / [[251, 108], [73, 496]], * Val accuracy / confusion: 73.90% / [[136, 94], [60, 300]] ------------------------------ Epoch 207 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.270581 - Iter 028 / 029, Loss: 0.456476 * Train accuracy / confusion: 81.36% / [[261, 100], [73, 494]], * Val accuracy / confusion: 73.22% / [[133, 97], [61, 299]] ------------------------------ Epoch 208 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.387242 - Iter 028 / 029, Loss: 0.480956 * Train accuracy / confusion: 81.68% / [[260, 100], [70, 498]], * Val accuracy / confusion: 75.25% / [[147, 83], [63, 297]] ------------------------------ Epoch 209 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.454833 - Iter 028 / 029, Loss: 0.618584 * Train accuracy / confusion: 79.85% / [[253, 112], [75, 488]], * Val accuracy / confusion: 72.54% / [[138, 92], [70, 290]] ------------------------------ Epoch 210 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.519991 - Iter 028 / 029, Loss: 0.339503 * Train accuracy / confusion: 81.68% / [[272, 94], [76, 486]], * Val accuracy / confusion: 73.73% / [[144, 86], [69, 291]] ------------------------------ Epoch 211 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.357003 - Iter 028 / 029, Loss: 0.505451 * Train accuracy / confusion: 82.44% / [[265, 96], [67, 500]], * Val accuracy / confusion: 72.71% / [[133, 97], [64, 296]] ------------------------------ Epoch 212 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.303015 - Iter 028 / 029, Loss: 0.457311 * Train accuracy / confusion: 82.76% / [[266, 96], [64, 502]], * Val accuracy / confusion: 74.07% / [[142, 88], [65, 295]] ------------------------------ Epoch 213 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.357668 - Iter 028 / 029, Loss: 0.314535 * Train accuracy / confusion: 80.17% / [[253, 109], [75, 491]], * Val accuracy / confusion: 75.25% / [[145, 85], [61, 299]] ------------------------------ Epoch 214 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.557974 - Iter 028 / 029, Loss: 0.337525 * Train accuracy / confusion: 81.79% / [[260, 105], [64, 499]], * Val accuracy / confusion: 76.44% / [[145, 85], [54, 306]] ------------------------------ Epoch 215 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.469432 - Iter 028 / 029, Loss: 0.364401 * Train accuracy / confusion: 81.79% / [[263, 99], [70, 496]], * Val accuracy / confusion: 75.59% / [[142, 88], [56, 304]] ------------------------------ Epoch 216 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.428869 - Iter 028 / 029, Loss: 0.434341 * Train accuracy / confusion: 79.74% / [[258, 105], [83, 482]], * Val accuracy / confusion: 74.24% / [[145, 85], [67, 293]] ------------------------------ Epoch 217 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.524284 - Iter 028 / 029, Loss: 0.310029 * Train accuracy / confusion: 81.25% / [[256, 103], [71, 498]], * Val accuracy / confusion: 72.03% / [[141, 89], [76, 284]] ------------------------------ Epoch 218 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.329755 - Iter 028 / 029, Loss: 0.505493 * Train accuracy / confusion: 80.60% / [[258, 107], [73, 490]], * Val accuracy / confusion: 73.22% / [[133, 97], [61, 299]] ------------------------------ Epoch 219 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.410676 - Iter 028 / 029, Loss: 0.420133 * Train accuracy / confusion: 80.17% / [[245, 116], [68, 499]], * Val accuracy / confusion: 70.34% / [[125, 105], [70, 290]] ------------------------------ Epoch 220 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.559369 - Iter 028 / 029, Loss: 0.407940 * Train accuracy / confusion: 80.82% / [[263, 100], [78, 487]], * Val accuracy / confusion: 74.24% / [[147, 83], [69, 291]] ------------------------------ Epoch 221 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.463668 - Iter 028 / 029, Loss: 0.326558 * Train accuracy / confusion: 83.30% / [[265, 99], [56, 508]], * Val accuracy / confusion: 74.24% / [[143, 87], [65, 295]] ------------------------------ Epoch 222 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.359013 - Iter 028 / 029, Loss: 0.515643 * Train accuracy / confusion: 80.60% / [[265, 100], [80, 483]], * Val accuracy / confusion: 76.95% / [[155, 75], [61, 299]] ------------------------------ Epoch 223 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.265731 - Iter 028 / 029, Loss: 0.377244 * Train accuracy / confusion: 81.47% / [[265, 96], [76, 491]], * Val accuracy / confusion: 74.41% / [[136, 94], [57, 303]] ------------------------------ Epoch 224 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.563402 - Iter 028 / 029, Loss: 0.383899 * Train accuracy / confusion: 80.39% / [[253, 107], [75, 493]], * Val accuracy / confusion: 72.88% / [[136, 94], [66, 294]] ------------------------------ Epoch 225 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.381814 - Iter 028 / 029, Loss: 0.482833 * Train accuracy / confusion: 79.42% / [[249, 111], [80, 488]], * Val accuracy / confusion: 74.92% / [[141, 89], [59, 301]] ------------------------------ Epoch 226 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.421582 - Iter 028 / 029, Loss: 0.377082 * Train accuracy / confusion: 80.71% / [[254, 108], [71, 495]], * Val accuracy / confusion: 75.93% / [[145, 85], [57, 303]] ------------------------------ Epoch 227 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.476843 - Iter 028 / 029, Loss: 0.452611 * Train accuracy / confusion: 82.33% / [[257, 106], [58, 507]], * Val accuracy / confusion: 74.58% / [[148, 82], [68, 292]] ------------------------------ Epoch 228 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.423557 - Iter 028 / 029, Loss: 0.496105 * Train accuracy / confusion: 80.50% / [[249, 113], [68, 498]], * Val accuracy / confusion: 74.24% / [[132, 98], [54, 306]] ------------------------------ Epoch 229 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.451671 - Iter 028 / 029, Loss: 0.341423 * Train accuracy / confusion: 81.25% / [[261, 99], [75, 493]], * Val accuracy / confusion: 72.88% / [[143, 87], [73, 287]] ------------------------------ Epoch 230 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.243721 - Iter 028 / 029, Loss: 0.489110 * Train accuracy / confusion: 81.57% / [[259, 103], [68, 498]], * Val accuracy / confusion: 73.05% / [[141, 89], [70, 290]] ------------------------------ Epoch 231 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.618569 - Iter 028 / 029, Loss: 0.583650 * Train accuracy / confusion: 81.36% / [[256, 107], [66, 499]], * Val accuracy / confusion: 72.03% / [[134, 96], [69, 291]] ------------------------------ Epoch 232 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.434861 - Iter 028 / 029, Loss: 0.282559 * Train accuracy / confusion: 80.39% / [[251, 111], [71, 495]], * Val accuracy / confusion: 73.22% / [[133, 97], [61, 299]] ------------------------------ Epoch 233 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.610155 - Iter 028 / 029, Loss: 0.387109 * Train accuracy / confusion: 81.36% / [[254, 106], [67, 501]], * Val accuracy / confusion: 74.24% / [[133, 97], [55, 305]] ------------------------------ Epoch 234 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.516213 - Iter 028 / 029, Loss: 0.286285 * Train accuracy / confusion: 80.60% / [[256, 108], [72, 492]], * Val accuracy / confusion: 76.44% / [[135, 95], [44, 316]] ------------------------------ Epoch 235 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.323027 - Iter 028 / 029, Loss: 0.438876 * Train accuracy / confusion: 80.93% / [[246, 113], [64, 505]], * Val accuracy / confusion: 73.05% / [[141, 89], [70, 290]] ------------------------------ Epoch 236 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.363482 - Iter 028 / 029, Loss: 0.375049 * Train accuracy / confusion: 82.44% / [[262, 102], [61, 503]], * Val accuracy / confusion: 74.92% / [[137, 93], [55, 305]] ------------------------------ Epoch 237 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.441195 - Iter 028 / 029, Loss: 0.438187 * Train accuracy / confusion: 79.74% / [[255, 109], [79, 485]], * Val accuracy / confusion: 72.37% / [[132, 98], [65, 295]] ------------------------------ Epoch 238 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.374604 - Iter 028 / 029, Loss: 0.497436 * Train accuracy / confusion: 83.08% / [[274, 91], [66, 497]], * Val accuracy / confusion: 71.19% / [[136, 94], [76, 284]] ------------------------------ Epoch 239 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.384731 - Iter 028 / 029, Loss: 0.533647 * Train accuracy / confusion: 80.82% / [[253, 107], [71, 497]], * Val accuracy / confusion: 75.08% / [[142, 88], [59, 301]] ------------------------------ Epoch 240 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.232499 - Iter 028 / 029, Loss: 0.361558 * Train accuracy / confusion: 82.76% / [[270, 95], [65, 498]], * Val accuracy / confusion: 74.75% / [[135, 95], [54, 306]] ------------------------------ Epoch 241 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.465575 - Iter 028 / 029, Loss: 0.396879 * Train accuracy / confusion: 82.00% / [[260, 101], [66, 501]], * Val accuracy / confusion: 71.02% / [[130, 100], [71, 289]] ------------------------------ Epoch 242 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.398045 - Iter 028 / 029, Loss: 0.445105 * Train accuracy / confusion: 82.00% / [[254, 106], [61, 507]], * Val accuracy / confusion: 73.56% / [[140, 90], [66, 294]] ------------------------------ Epoch 243 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.356570 - Iter 028 / 029, Loss: 0.303727 * Train accuracy / confusion: 82.11% / [[262, 99], [67, 500]], * Val accuracy / confusion: 74.41% / [[133, 97], [54, 306]] ------------------------------ Epoch 244 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.674222 - Iter 028 / 029, Loss: 0.474916 * Train accuracy / confusion: 82.33% / [[261, 98], [66, 503]], * Val accuracy / confusion: 73.39% / [[136, 94], [63, 297]] ------------------------------ Epoch 245 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.321479 - Iter 028 / 029, Loss: 0.304345 * Train accuracy / confusion: 81.68% / [[265, 98], [72, 493]], * Val accuracy / confusion: 72.71% / [[143, 87], [74, 286]] ------------------------------ Epoch 246 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.446204 - Iter 028 / 029, Loss: 0.372905 * Train accuracy / confusion: 81.47% / [[262, 100], [72, 494]], * Val accuracy / confusion: 75.08% / [[145, 85], [62, 298]] ------------------------------ Epoch 247 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.423181 - Iter 028 / 029, Loss: 0.369086 * Train accuracy / confusion: 82.44% / [[258, 104], [59, 507]], * Val accuracy / confusion: 75.08% / [[136, 94], [53, 307]] ------------------------------ Epoch 248 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.382381 - Iter 028 / 029, Loss: 0.404743 * Train accuracy / confusion: 80.93% / [[253, 110], [67, 498]], * Val accuracy / confusion: 74.24% / [[137, 93], [59, 301]] ------------------------------ Epoch 249 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.463575 - Iter 028 / 029, Loss: 0.422289 * Train accuracy / confusion: 81.36% / [[258, 104], [69, 497]], * Val accuracy / confusion: 75.08% / [[144, 86], [61, 299]] ------------------------------ Epoch 250 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.317098 - Iter 028 / 029, Loss: 0.377977 * Train accuracy / confusion: 80.93% / [[254, 108], [69, 497]], * Val accuracy / confusion: 74.75% / [[149, 81], [68, 292]] ------------------------------ Epoch 251 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.392462 - Iter 028 / 029, Loss: 0.495149 * Train accuracy / confusion: 79.74% / [[252, 112], [76, 488]], * Val accuracy / confusion: 75.25% / [[155, 75], [71, 289]] ------------------------------ Epoch 252 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.550073 - Iter 028 / 029, Loss: 0.517115 * Train accuracy / confusion: 81.14% / [[254, 108], [67, 499]], * Val accuracy / confusion: 73.90% / [[139, 91], [63, 297]] ------------------------------ Epoch 253 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.394454 - Iter 028 / 029, Loss: 0.488929 * Train accuracy / confusion: 83.08% / [[258, 101], [56, 513]], * Val accuracy / confusion: 73.56% / [[132, 98], [58, 302]] ------------------------------ Epoch 254 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.529237 - Iter 028 / 029, Loss: 0.417212 * Train accuracy / confusion: 80.82% / [[256, 107], [71, 494]], * Val accuracy / confusion: 73.56% / [[136, 94], [62, 298]] ------------------------------ Epoch 255 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.435786 - Iter 028 / 029, Loss: 0.366123 * Train accuracy / confusion: 81.68% / [[256, 106], [64, 502]], * Val accuracy / confusion: 74.24% / [[149, 81], [71, 289]] ------------------------------ Epoch 256 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.399375 - Iter 028 / 029, Loss: 0.667273 * Train accuracy / confusion: 81.79% / [[260, 98], [71, 499]], * Val accuracy / confusion: 71.86% / [[137, 93], [73, 287]] ------------------------------ Epoch 257 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.329478 - Iter 028 / 029, Loss: 0.470293 * Train accuracy / confusion: 83.08% / [[268, 93], [64, 503]], * Val accuracy / confusion: 72.20% / [[147, 83], [81, 279]] ------------------------------ Epoch 258 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.449004 - Iter 028 / 029, Loss: 0.494499 * Train accuracy / confusion: 80.82% / [[257, 106], [72, 493]], * Val accuracy / confusion: 74.24% / [[143, 87], [65, 295]] ------------------------------ Epoch 259 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.428926 - Iter 028 / 029, Loss: 0.323434 * Train accuracy / confusion: 81.57% / [[251, 108], [63, 506]], * Val accuracy / confusion: 72.37% / [[133, 97], [66, 294]] ------------------------------ Epoch 260 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.315012 - Iter 028 / 029, Loss: 0.278288 * Train accuracy / confusion: 82.00% / [[256, 104], [63, 505]], * Val accuracy / confusion: 74.41% / [[141, 89], [62, 298]] ------------------------------ Epoch 261 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.479479 - Iter 028 / 029, Loss: 0.438306 * Train accuracy / confusion: 81.57% / [[254, 109], [62, 503]], * Val accuracy / confusion: 75.08% / [[135, 95], [52, 308]] ------------------------------ Epoch 262 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.248718 - Iter 028 / 029, Loss: 0.417217 * Train accuracy / confusion: 82.33% / [[268, 94], [70, 496]], * Val accuracy / confusion: 74.41% / [[141, 89], [62, 298]] ------------------------------ Epoch 263 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.231087 - Iter 028 / 029, Loss: 0.372590 * Train accuracy / confusion: 82.22% / [[266, 96], [69, 497]], * Val accuracy / confusion: 74.92% / [[141, 89], [59, 301]] ------------------------------ Epoch 264 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.303024 - Iter 028 / 029, Loss: 0.393750 * Train accuracy / confusion: 81.14% / [[259, 102], [73, 494]], * Val accuracy / confusion: 73.22% / [[142, 88], [70, 290]] ------------------------------ Epoch 265 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.320704 - Iter 028 / 029, Loss: 0.377415 * Train accuracy / confusion: 82.65% / [[272, 88], [73, 495]], * Val accuracy / confusion: 74.75% / [[141, 89], [60, 300]] ------------------------------ Epoch 266 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.383276 - Iter 028 / 029, Loss: 0.397758 * Train accuracy / confusion: 81.57% / [[255, 108], [63, 502]], * Val accuracy / confusion: 73.56% / [[137, 93], [63, 297]] ------------------------------ Epoch 267 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.411986 - Iter 028 / 029, Loss: 0.382159 * Train accuracy / confusion: 82.11% / [[262, 98], [68, 500]], * Val accuracy / confusion: 74.24% / [[146, 84], [68, 292]] ------------------------------ Epoch 268 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.744511 - Iter 028 / 029, Loss: 0.357676 * Train accuracy / confusion: 81.79% / [[265, 95], [74, 494]], * Val accuracy / confusion: 75.59% / [[147, 83], [61, 299]] ------------------------------ Epoch 269 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.404542 - Iter 028 / 029, Loss: 0.545426 * Train accuracy / confusion: 81.03% / [[254, 108], [68, 498]], * Val accuracy / confusion: 73.73% / [[135, 95], [60, 300]] ------------------------------ Epoch 270 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.347640 - Iter 028 / 029, Loss: 0.500181 * Train accuracy / confusion: 81.47% / [[263, 100], [72, 493]], * Val accuracy / confusion: 73.05% / [[128, 102], [57, 303]] ------------------------------ Epoch 271 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.335860 - Iter 028 / 029, Loss: 0.425540 * Train accuracy / confusion: 84.05% / [[283, 81], [67, 497]], * Val accuracy / confusion: 72.37% / [[125, 105], [58, 302]] ------------------------------ Epoch 272 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.409071 - Iter 028 / 029, Loss: 0.421352 * Train accuracy / confusion: 82.54% / [[263, 93], [69, 503]], * Val accuracy / confusion: 73.39% / [[143, 87], [70, 290]] ------------------------------ Epoch 273 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.434837 - Iter 028 / 029, Loss: 0.348006 * Train accuracy / confusion: 82.65% / [[271, 91], [70, 496]], * Val accuracy / confusion: 74.24% / [[133, 97], [55, 305]] ------------------------------ Epoch 274 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.613793 - Iter 028 / 029, Loss: 0.342916 * Train accuracy / confusion: 81.25% / [[255, 103], [71, 499]], * Val accuracy / confusion: 72.88% / [[140, 90], [70, 290]] ------------------------------ Epoch 275 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.395804 - Iter 028 / 029, Loss: 0.542413 * Train accuracy / confusion: 80.06% / [[254, 110], [75, 489]], * Val accuracy / confusion: 74.07% / [[139, 91], [62, 298]] ------------------------------ Epoch 276 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.469755 - Iter 028 / 029, Loss: 0.231150 * Train accuracy / confusion: 80.93% / [[262, 100], [77, 489]], * Val accuracy / confusion: 73.90% / [[137, 93], [61, 299]] ------------------------------ Epoch 277 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.294869 - Iter 028 / 029, Loss: 0.299100 * Train accuracy / confusion: 82.00% / [[259, 104], [63, 502]], * Val accuracy / confusion: 74.58% / [[137, 93], [57, 303]] ------------------------------ Epoch 278 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.710671 - Iter 028 / 029, Loss: 0.345702 * Train accuracy / confusion: 81.14% / [[257, 102], [73, 496]], * Val accuracy / confusion: 72.54% / [[133, 97], [65, 295]] ------------------------------ Epoch 279 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.750672 - Iter 028 / 029, Loss: 0.428681 * Train accuracy / confusion: 81.25% / [[261, 103], [71, 493]], * Val accuracy / confusion: 74.41% / [[148, 82], [69, 291]] ------------------------------ Epoch 280 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.365510 - Iter 028 / 029, Loss: 0.367238 * Train accuracy / confusion: 82.11% / [[267, 94], [72, 495]], * Val accuracy / confusion: 74.41% / [[141, 89], [62, 298]] ------------------------------ Epoch 281 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.466812 - Iter 028 / 029, Loss: 0.339517 * Train accuracy / confusion: 80.71% / [[250, 111], [68, 499]], * Val accuracy / confusion: 75.08% / [[144, 86], [61, 299]] ------------------------------ Epoch 282 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.378161 - Iter 028 / 029, Loss: 0.443349 * Train accuracy / confusion: 82.54% / [[272, 92], [70, 494]], * Val accuracy / confusion: 75.25% / [[153, 77], [69, 291]] ------------------------------ Epoch 283 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.374574 - Iter 028 / 029, Loss: 0.342573 * Train accuracy / confusion: 82.44% / [[260, 97], [66, 505]], * Val accuracy / confusion: 75.42% / [[144, 86], [59, 301]] ------------------------------ Epoch 284 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.661330 - Iter 028 / 029, Loss: 0.360402 * Train accuracy / confusion: 82.44% / [[268, 95], [68, 497]], * Val accuracy / confusion: 72.20% / [[141, 89], [75, 285]] ------------------------------ Epoch 285 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.397526 - Iter 028 / 029, Loss: 0.482001 * Train accuracy / confusion: 81.14% / [[251, 107], [68, 502]], * Val accuracy / confusion: 74.41% / [[145, 85], [66, 294]] ------------------------------ Epoch 286 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.320460 - Iter 028 / 029, Loss: 0.248434 * Train accuracy / confusion: 83.19% / [[265, 93], [63, 507]], * Val accuracy / confusion: 72.88% / [[141, 89], [71, 289]] ------------------------------ Epoch 287 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.300815 - Iter 028 / 029, Loss: 0.366178 * Train accuracy / confusion: 83.30% / [[267, 93], [62, 506]], * Val accuracy / confusion: 74.07% / [[136, 94], [59, 301]] ------------------------------ Epoch 288 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.415670 - Iter 028 / 029, Loss: 0.406994 * Train accuracy / confusion: 80.71% / [[252, 106], [73, 497]], * Val accuracy / confusion: 72.54% / [[136, 94], [68, 292]] ------------------------------ Epoch 289 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.563677 - Iter 028 / 029, Loss: 0.312169 * Train accuracy / confusion: 81.03% / [[264, 95], [81, 488]], * Val accuracy / confusion: 73.56% / [[130, 100], [56, 304]] ------------------------------ Epoch 290 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.197825 - Iter 028 / 029, Loss: 0.295744 * Train accuracy / confusion: 83.51% / [[272, 92], [61, 503]], * Val accuracy / confusion: 74.07% / [[143, 87], [66, 294]] ------------------------------ Epoch 291 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.349110 - Iter 028 / 029, Loss: 0.385926 * Train accuracy / confusion: 82.54% / [[267, 97], [65, 499]], * Val accuracy / confusion: 73.73% / [[138, 92], [63, 297]] ------------------------------ Epoch 292 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.450711 - Iter 028 / 029, Loss: 0.285046 * Train accuracy / confusion: 82.54% / [[263, 98], [64, 503]], * Val accuracy / confusion: 74.07% / [[151, 79], [74, 286]] ------------------------------ Epoch 293 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.456495 - Iter 028 / 029, Loss: 0.365253 * Train accuracy / confusion: 83.73% / [[282, 82], [69, 495]], * Val accuracy / confusion: 74.58% / [[147, 83], [67, 293]] ------------------------------ Epoch 294 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.305242 - Iter 028 / 029, Loss: 0.555290 * Train accuracy / confusion: 82.76% / [[260, 102], [58, 508]], * Val accuracy / confusion: 71.36% / [[138, 92], [77, 283]] ------------------------------ Epoch 295 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.255228 - Iter 028 / 029, Loss: 0.329850 * Train accuracy / confusion: 83.62% / [[264, 100], [52, 512]], * Val accuracy / confusion: 73.73% / [[143, 87], [68, 292]] ------------------------------ Epoch 296 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.279157 - Iter 028 / 029, Loss: 0.226873 * Train accuracy / confusion: 82.00% / [[268, 96], [71, 493]], * Val accuracy / confusion: 74.75% / [[153, 77], [72, 288]] ------------------------------ Epoch 297 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.520353 - Iter 028 / 029, Loss: 0.247773 * Train accuracy / confusion: 80.50% / [[254, 106], [75, 493]], * Val accuracy / confusion: 73.56% / [[137, 93], [63, 297]] ------------------------------ Epoch 298 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.343391 - Iter 028 / 029, Loss: 0.502420 * Train accuracy / confusion: 82.97% / [[270, 91], [67, 500]], * Val accuracy / confusion: 75.42% / [[144, 86], [59, 301]] ------------------------------ Epoch 299 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.356560 - Iter 028 / 029, Loss: 0.324595 * Train accuracy / confusion: 80.50% / [[254, 108], [73, 493]], * Val accuracy / confusion: 74.41% / [[154, 76], [75, 285]] ------------------------------ Epoch 300 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.325108 - Iter 028 / 029, Loss: 0.344490 * Train accuracy / confusion: 81.03% / [[256, 107], [69, 496]], * Val accuracy / confusion: 74.75% / [[136, 94], [55, 305]] ------------------------------ Epoch 301 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.492291 - Iter 028 / 029, Loss: 0.310246 * Train accuracy / confusion: 82.76% / [[271, 90], [70, 497]], * Val accuracy / confusion: 73.73% / [[144, 86], [69, 291]] ------------------------------ Epoch 302 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.244296 - Iter 028 / 029, Loss: 0.263494 * Train accuracy / confusion: 82.65% / [[268, 97], [64, 499]], * Val accuracy / confusion: 70.85% / [[132, 98], [74, 286]] ------------------------------ Epoch 303 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.315983 - Iter 028 / 029, Loss: 0.419942 * Train accuracy / confusion: 80.93% / [[260, 103], [74, 491]], * Val accuracy / confusion: 74.41% / [[145, 85], [66, 294]] ------------------------------ Epoch 304 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.561379 - Iter 028 / 029, Loss: 0.254883 * Train accuracy / confusion: 83.51% / [[262, 99], [54, 513]], * Val accuracy / confusion: 73.73% / [[131, 99], [56, 304]] ------------------------------ Epoch 305 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.365644 - Iter 028 / 029, Loss: 0.598550 * Train accuracy / confusion: 82.44% / [[274, 90], [73, 491]], * Val accuracy / confusion: 73.39% / [[147, 83], [74, 286]] ------------------------------ Epoch 306 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.497691 - Iter 028 / 029, Loss: 0.248090 * Train accuracy / confusion: 82.54% / [[265, 101], [61, 501]], * Val accuracy / confusion: 74.41% / [[145, 85], [66, 294]] ------------------------------ Epoch 307 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.471675 - Iter 028 / 029, Loss: 0.444409 * Train accuracy / confusion: 83.08% / [[265, 94], [63, 506]], * Val accuracy / confusion: 72.54% / [[138, 92], [70, 290]] ------------------------------ Epoch 308 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.422741 - Iter 028 / 029, Loss: 0.317313 * Train accuracy / confusion: 82.76% / [[266, 98], [62, 502]], * Val accuracy / confusion: 74.24% / [[142, 88], [64, 296]] ------------------------------ Epoch 309 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.616941 - Iter 028 / 029, Loss: 0.375898 * Train accuracy / confusion: 82.00% / [[266, 96], [71, 495]], * Val accuracy / confusion: 73.05% / [[136, 94], [65, 295]] ------------------------------ Epoch 310 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.468910 - Iter 028 / 029, Loss: 0.449264 * Train accuracy / confusion: 81.79% / [[260, 98], [71, 499]], * Val accuracy / confusion: 72.03% / [[139, 91], [74, 286]] ------------------------------ Epoch 311 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.446014 - Iter 028 / 029, Loss: 0.399025 * Train accuracy / confusion: 83.84% / [[271, 88], [62, 507]], * Val accuracy / confusion: 73.56% / [[135, 95], [61, 299]] ------------------------------ Epoch 312 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.373220 - Iter 028 / 029, Loss: 0.313577 * Train accuracy / confusion: 81.14% / [[260, 100], [75, 493]], * Val accuracy / confusion: 73.39% / [[131, 99], [58, 302]] ------------------------------ Epoch 313 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.402473 - Iter 028 / 029, Loss: 0.543449 * Train accuracy / confusion: 82.00% / [[266, 95], [72, 495]], * Val accuracy / confusion: 73.90% / [[138, 92], [62, 298]] ------------------------------ Epoch 314 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.386908 - Iter 028 / 029, Loss: 0.638304 * Train accuracy / confusion: 82.11% / [[263, 99], [67, 499]], * Val accuracy / confusion: 75.42% / [[133, 97], [48, 312]] ------------------------------ Epoch 315 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.502390 - Iter 028 / 029, Loss: 0.449752 * Train accuracy / confusion: 80.82% / [[260, 103], [75, 490]], * Val accuracy / confusion: 73.56% / [[138, 92], [64, 296]] ------------------------------ Epoch 316 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.315583 - Iter 028 / 029, Loss: 0.363860 * Train accuracy / confusion: 81.79% / [[270, 90], [79, 489]], * Val accuracy / confusion: 71.36% / [[137, 93], [76, 284]] ------------------------------ Epoch 317 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.262527 - Iter 028 / 029, Loss: 0.489050 * Train accuracy / confusion: 81.57% / [[258, 106], [65, 499]], * Val accuracy / confusion: 72.03% / [[143, 87], [78, 282]] ------------------------------ Epoch 318 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.377674 - Iter 028 / 029, Loss: 0.417116 * Train accuracy / confusion: 82.76% / [[272, 87], [73, 496]], * Val accuracy / confusion: 75.59% / [[144, 86], [58, 302]] ------------------------------ Epoch 319 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.492442 - Iter 028 / 029, Loss: 0.316327 * Train accuracy / confusion: 82.33% / [[260, 102], [62, 504]], * Val accuracy / confusion: 74.58% / [[145, 85], [65, 295]] ------------------------------ Epoch 320 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.326487 - Iter 028 / 029, Loss: 0.317429 * Train accuracy / confusion: 83.08% / [[272, 92], [65, 499]], * Val accuracy / confusion: 72.88% / [[131, 99], [61, 299]] ------------------------------ Epoch 321 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.427779 - Iter 028 / 029, Loss: 0.551862 * Train accuracy / confusion: 83.51% / [[279, 82], [71, 496]], * Val accuracy / confusion: 72.37% / [[156, 74], [89, 271]] ------------------------------ Epoch 322 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.446123 - Iter 028 / 029, Loss: 0.331299 * Train accuracy / confusion: 81.36% / [[253, 106], [67, 502]], * Val accuracy / confusion: 76.61% / [[143, 87], [51, 309]] ------------------------------ Epoch 323 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.252785 - Iter 028 / 029, Loss: 0.379604 * Train accuracy / confusion: 82.00% / [[259, 104], [63, 502]], * Val accuracy / confusion: 75.42% / [[136, 94], [51, 309]] ------------------------------ Epoch 324 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.367172 - Iter 028 / 029, Loss: 0.324398 * Train accuracy / confusion: 83.30% / [[272, 93], [62, 501]], * Val accuracy / confusion: 72.88% / [[134, 96], [64, 296]] ------------------------------ Epoch 325 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.300369 - Iter 028 / 029, Loss: 0.225753 * Train accuracy / confusion: 83.30% / [[270, 90], [65, 503]], * Val accuracy / confusion: 73.05% / [[143, 87], [72, 288]] ------------------------------ Epoch 326 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.433793 - Iter 028 / 029, Loss: 0.368305 * Train accuracy / confusion: 81.79% / [[262, 97], [72, 497]], * Val accuracy / confusion: 72.71% / [[143, 87], [74, 286]] ------------------------------ Epoch 327 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.301440 - Iter 028 / 029, Loss: 0.342465 * Train accuracy / confusion: 82.33% / [[264, 95], [69, 500]], * Val accuracy / confusion: 74.58% / [[146, 84], [66, 294]] ------------------------------ Epoch 328 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.652461 - Iter 028 / 029, Loss: 0.300239 * Train accuracy / confusion: 82.87% / [[264, 101], [58, 505]], * Val accuracy / confusion: 74.07% / [[129, 101], [52, 308]] ------------------------------ Epoch 329 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.597035 - Iter 028 / 029, Loss: 0.329248 * Train accuracy / confusion: 82.33% / [[262, 99], [65, 502]], * Val accuracy / confusion: 74.58% / [[136, 94], [56, 304]] ------------------------------ Epoch 330 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.463926 - Iter 028 / 029, Loss: 0.190719 * Train accuracy / confusion: 82.65% / [[271, 94], [67, 496]], * Val accuracy / confusion: 75.25% / [[141, 89], [57, 303]] ------------------------------ Epoch 331 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.472015 - Iter 028 / 029, Loss: 0.345598 * Train accuracy / confusion: 83.41% / [[275, 86], [68, 499]], * Val accuracy / confusion: 75.93% / [[144, 86], [56, 304]] ------------------------------ Epoch 332 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.427939 - Iter 028 / 029, Loss: 0.406955 * Train accuracy / confusion: 80.17% / [[253, 110], [74, 491]], * Val accuracy / confusion: 74.58% / [[139, 91], [59, 301]] ------------------------------ Epoch 333 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.407258 - Iter 028 / 029, Loss: 0.415635 * Train accuracy / confusion: 81.14% / [[261, 103], [72, 492]], * Val accuracy / confusion: 74.92% / [[151, 79], [69, 291]] ------------------------------ Epoch 334 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.343187 - Iter 028 / 029, Loss: 0.489969 * Train accuracy / confusion: 81.36% / [[260, 102], [71, 495]], * Val accuracy / confusion: 74.24% / [[141, 89], [63, 297]] ------------------------------ Epoch 335 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.250982 - Iter 028 / 029, Loss: 0.345752 * Train accuracy / confusion: 82.44% / [[266, 97], [66, 499]], * Val accuracy / confusion: 75.25% / [[150, 80], [66, 294]] ------------------------------ Epoch 336 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.268095 - Iter 028 / 029, Loss: 0.473167 * Train accuracy / confusion: 81.90% / [[258, 106], [62, 502]], * Val accuracy / confusion: 73.22% / [[139, 91], [67, 293]] ------------------------------ Epoch 337 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.287134 - Iter 028 / 029, Loss: 0.351693 * Train accuracy / confusion: 83.51% / [[265, 98], [55, 510]], * Val accuracy / confusion: 76.27% / [[149, 81], [59, 301]] ------------------------------ Epoch 338 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.407420 - Iter 028 / 029, Loss: 0.208462 * Train accuracy / confusion: 82.87% / [[262, 97], [62, 507]], * Val accuracy / confusion: 75.25% / [[152, 78], [68, 292]] ------------------------------ Epoch 339 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.421624 - Iter 028 / 029, Loss: 0.469149 * Train accuracy / confusion: 82.44% / [[264, 95], [68, 501]], * Val accuracy / confusion: 74.07% / [[144, 86], [67, 293]] ------------------------------ Epoch 340 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.376328 - Iter 028 / 029, Loss: 0.526497 * Train accuracy / confusion: 82.33% / [[267, 98], [66, 497]], * Val accuracy / confusion: 74.07% / [[136, 94], [59, 301]] ------------------------------ Epoch 341 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.382890 - Iter 028 / 029, Loss: 0.507121 * Train accuracy / confusion: 83.84% / [[274, 90], [60, 504]], * Val accuracy / confusion: 73.22% / [[137, 93], [65, 295]] ------------------------------ Epoch 342 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.403861 - Iter 028 / 029, Loss: 0.253060 * Train accuracy / confusion: 82.22% / [[268, 90], [75, 495]], * Val accuracy / confusion: 73.56% / [[143, 87], [69, 291]] ------------------------------ Epoch 343 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.305795 - Iter 028 / 029, Loss: 0.355011 * Train accuracy / confusion: 81.68% / [[263, 100], [70, 495]], * Val accuracy / confusion: 72.54% / [[134, 96], [66, 294]] ------------------------------ Epoch 344 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.267009 - Iter 028 / 029, Loss: 0.337394 * Train accuracy / confusion: 81.90% / [[261, 100], [68, 499]], * Val accuracy / confusion: 75.42% / [[137, 93], [52, 308]] ------------------------------ Epoch 345 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.481018 - Iter 028 / 029, Loss: 0.362971 * Train accuracy / confusion: 84.05% / [[282, 81], [67, 498]], * Val accuracy / confusion: 74.24% / [[151, 79], [73, 287]] ------------------------------ Epoch 346 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.366798 - Iter 028 / 029, Loss: 0.447629 * Train accuracy / confusion: 82.65% / [[265, 97], [64, 502]], * Val accuracy / confusion: 73.73% / [[144, 86], [69, 291]] ------------------------------ Epoch 347 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.718011 - Iter 028 / 029, Loss: 0.369339 * Train accuracy / confusion: 82.11% / [[263, 101], [65, 499]], * Val accuracy / confusion: 74.07% / [[143, 87], [66, 294]] ------------------------------ Epoch 348 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.542391 - Iter 028 / 029, Loss: 0.535678 * Train accuracy / confusion: 81.90% / [[266, 92], [76, 494]], * Val accuracy / confusion: 74.41% / [[147, 83], [68, 292]] ------------------------------ Epoch 349 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.329353 - Iter 028 / 029, Loss: 0.389588 * Train accuracy / confusion: 81.25% / [[262, 103], [71, 492]], * Val accuracy / confusion: 72.37% / [[136, 94], [69, 291]] ------------------------------ Epoch 350 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.288106 - Iter 028 / 029, Loss: 0.249224 * Train accuracy / confusion: 84.59% / [[270, 93], [50, 515]], * Val accuracy / confusion: 75.59% / [[143, 87], [57, 303]] ------------------------------ Epoch 351 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.361662 - Iter 028 / 029, Loss: 0.471099 * Train accuracy / confusion: 82.22% / [[268, 97], [68, 495]], * Val accuracy / confusion: 71.02% / [[141, 89], [82, 278]] ------------------------------ Epoch 352 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.501525 - Iter 028 / 029, Loss: 0.331133 * Train accuracy / confusion: 82.87% / [[269, 90], [69, 500]], * Val accuracy / confusion: 73.90% / [[144, 86], [68, 292]] ------------------------------ Epoch 353 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.407159 - Iter 028 / 029, Loss: 0.279026 * Train accuracy / confusion: 81.79% / [[264, 98], [71, 495]], * Val accuracy / confusion: 73.90% / [[146, 84], [70, 290]] ------------------------------ Epoch 354 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.380334 - Iter 028 / 029, Loss: 0.466162 * Train accuracy / confusion: 82.33% / [[271, 96], [68, 493]], * Val accuracy / confusion: 74.75% / [[141, 89], [60, 300]] ------------------------------ Epoch 355 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.286727 - Iter 028 / 029, Loss: 0.304201 * Train accuracy / confusion: 83.73% / [[264, 97], [54, 513]], * Val accuracy / confusion: 74.92% / [[141, 89], [59, 301]] ------------------------------ Epoch 356 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.333764 - Iter 028 / 029, Loss: 0.292459 * Train accuracy / confusion: 82.76% / [[272, 93], [67, 496]], * Val accuracy / confusion: 73.22% / [[139, 91], [67, 293]] ------------------------------ Epoch 357 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.400503 - Iter 028 / 029, Loss: 0.487848 * Train accuracy / confusion: 84.16% / [[271, 91], [56, 510]], * Val accuracy / confusion: 74.24% / [[128, 102], [50, 310]] ------------------------------ Epoch 358 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.466222 - Iter 028 / 029, Loss: 0.427533 * Train accuracy / confusion: 83.51% / [[273, 90], [63, 502]], * Val accuracy / confusion: 74.07% / [[146, 84], [69, 291]] ------------------------------ Epoch 359 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.426810 - Iter 028 / 029, Loss: 0.355535 * Train accuracy / confusion: 82.22% / [[266, 95], [70, 497]], * Val accuracy / confusion: 74.41% / [[154, 76], [75, 285]] ------------------------------ Epoch 360 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.280633 - Iter 028 / 029, Loss: 0.236516 * Train accuracy / confusion: 83.62% / [[271, 88], [64, 505]], * Val accuracy / confusion: 75.93% / [[144, 86], [56, 304]] ------------------------------ Epoch 361 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.471954 - Iter 028 / 029, Loss: 0.349577 * Train accuracy / confusion: 82.65% / [[271, 92], [69, 496]], * Val accuracy / confusion: 71.02% / [[149, 81], [90, 270]] ------------------------------ Epoch 362 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.314676 - Iter 028 / 029, Loss: 0.425253 * Train accuracy / confusion: 83.84% / [[276, 87], [63, 502]], * Val accuracy / confusion: 73.22% / [[147, 83], [75, 285]] ------------------------------ Epoch 363 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.295172 - Iter 028 / 029, Loss: 0.228556 * Train accuracy / confusion: 83.19% / [[270, 92], [64, 502]], * Val accuracy / confusion: 74.58% / [[143, 87], [63, 297]] ------------------------------ Epoch 364 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.239452 - Iter 028 / 029, Loss: 0.320207 * Train accuracy / confusion: 82.65% / [[268, 92], [69, 499]], * Val accuracy / confusion: 73.90% / [[142, 88], [66, 294]] ------------------------------ Epoch 365 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.415354 - Iter 028 / 029, Loss: 0.367325 * Train accuracy / confusion: 81.68% / [[265, 98], [72, 493]], * Val accuracy / confusion: 74.41% / [[149, 81], [70, 290]] ------------------------------ Epoch 366 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.367193 - Iter 028 / 029, Loss: 0.391268 * Train accuracy / confusion: 82.22% / [[265, 100], [65, 498]], * Val accuracy / confusion: 73.73% / [[135, 95], [60, 300]] ------------------------------ Epoch 367 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.291423 - Iter 028 / 029, Loss: 0.336925 * Train accuracy / confusion: 81.47% / [[261, 101], [71, 495]], * Val accuracy / confusion: 71.53% / [[125, 105], [63, 297]] ------------------------------ Epoch 368 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.262772 - Iter 028 / 029, Loss: 0.535493 * Train accuracy / confusion: 83.08% / [[273, 89], [68, 498]], * Val accuracy / confusion: 74.58% / [[144, 86], [64, 296]] ------------------------------ Epoch 369 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.372668 - Iter 028 / 029, Loss: 0.277680 * Train accuracy / confusion: 82.11% / [[265, 95], [71, 497]], * Val accuracy / confusion: 72.37% / [[145, 85], [78, 282]] ------------------------------ Epoch 370 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.379174 - Iter 028 / 029, Loss: 0.432099 * Train accuracy / confusion: 83.08% / [[264, 96], [61, 507]], * Val accuracy / confusion: 72.71% / [[137, 93], [68, 292]] ------------------------------ Epoch 371 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.268536 - Iter 028 / 029, Loss: 0.424520 * Train accuracy / confusion: 82.97% / [[268, 95], [63, 502]], * Val accuracy / confusion: 74.24% / [[141, 89], [63, 297]] ------------------------------ Epoch 372 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.293233 - Iter 028 / 029, Loss: 0.368883 * Train accuracy / confusion: 83.19% / [[269, 93], [63, 503]], * Val accuracy / confusion: 73.39% / [[139, 91], [66, 294]] ------------------------------ Epoch 373 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.442047 - Iter 028 / 029, Loss: 0.486380 * Train accuracy / confusion: 82.22% / [[268, 92], [73, 495]], * Val accuracy / confusion: 73.73% / [[144, 86], [69, 291]] ------------------------------ Epoch 374 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.430139 - Iter 028 / 029, Loss: 0.400584 * Train accuracy / confusion: 82.11% / [[267, 98], [68, 495]], * Val accuracy / confusion: 73.05% / [[138, 92], [67, 293]] ------------------------------ Epoch 375 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.552635 - Iter 028 / 029, Loss: 0.356829 * Train accuracy / confusion: 80.50% / [[248, 113], [68, 499]], * Val accuracy / confusion: 72.20% / [[140, 90], [74, 286]] ------------------------------ Epoch 376 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.291544 - Iter 028 / 029, Loss: 0.412075 * Train accuracy / confusion: 85.13% / [[275, 86], [52, 515]], * Val accuracy / confusion: 73.90% / [[136, 94], [60, 300]] ------------------------------ Epoch 377 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.359077 - Iter 028 / 029, Loss: 0.287259 * Train accuracy / confusion: 84.27% / [[270, 91], [55, 512]], * Val accuracy / confusion: 73.90% / [[139, 91], [63, 297]] ------------------------------ Epoch 378 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.396199 - Iter 028 / 029, Loss: 0.397641 * Train accuracy / confusion: 82.97% / [[264, 98], [60, 506]], * Val accuracy / confusion: 71.53% / [[126, 104], [64, 296]] ------------------------------ Epoch 379 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.452631 - Iter 028 / 029, Loss: 0.416855 * Train accuracy / confusion: 83.19% / [[274, 92], [64, 498]], * Val accuracy / confusion: 73.22% / [[140, 90], [68, 292]] ------------------------------ Epoch 380 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.588578 - Iter 028 / 029, Loss: 0.461994 * Train accuracy / confusion: 83.94% / [[280, 85], [64, 499]], * Val accuracy / confusion: 74.58% / [[140, 90], [60, 300]] ------------------------------ Epoch 381 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.441516 - Iter 028 / 029, Loss: 0.416744 * Train accuracy / confusion: 82.54% / [[266, 97], [65, 500]], * Val accuracy / confusion: 75.59% / [[144, 86], [58, 302]] ------------------------------ Epoch 382 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.582318 - Iter 028 / 029, Loss: 0.700882 * Train accuracy / confusion: 82.65% / [[269, 93], [68, 498]], * Val accuracy / confusion: 73.39% / [[144, 86], [71, 289]] ------------------------------ Epoch 383 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.390024 - Iter 028 / 029, Loss: 0.462781 * Train accuracy / confusion: 82.44% / [[263, 102], [61, 502]], * Val accuracy / confusion: 72.20% / [[129, 101], [63, 297]] ------------------------------ Epoch 384 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.366930 - Iter 028 / 029, Loss: 0.281275 * Train accuracy / confusion: 81.90% / [[267, 97], [71, 493]], * Val accuracy / confusion: 72.37% / [[142, 88], [75, 285]] ------------------------------ Epoch 385 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.436013 - Iter 028 / 029, Loss: 0.402559 * Train accuracy / confusion: 82.54% / [[263, 95], [67, 503]], * Val accuracy / confusion: 75.08% / [[146, 84], [63, 297]] ------------------------------ Epoch 386 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.301831 - Iter 028 / 029, Loss: 0.388130 * Train accuracy / confusion: 82.87% / [[263, 100], [59, 506]], * Val accuracy / confusion: 73.39% / [[135, 95], [62, 298]] ------------------------------ Epoch 387 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.514098 - Iter 028 / 029, Loss: 0.259812 * Train accuracy / confusion: 82.87% / [[262, 101], [58, 507]], * Val accuracy / confusion: 73.56% / [[135, 95], [61, 299]] ------------------------------ Epoch 388 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.353788 - Iter 028 / 029, Loss: 0.320602 * Train accuracy / confusion: 82.44% / [[266, 96], [67, 499]], * Val accuracy / confusion: 72.03% / [[141, 89], [76, 284]] ------------------------------ Epoch 389 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.395485 - Iter 028 / 029, Loss: 0.418343 * Train accuracy / confusion: 82.11% / [[262, 100], [66, 500]], * Val accuracy / confusion: 73.39% / [[130, 100], [57, 303]] ------------------------------ Epoch 390 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.353766 - Iter 028 / 029, Loss: 0.257830 * Train accuracy / confusion: 83.62% / [[266, 92], [60, 510]], * Val accuracy / confusion: 72.37% / [[131, 99], [64, 296]] ------------------------------ Epoch 391 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.261809 - Iter 028 / 029, Loss: 0.653701 * Train accuracy / confusion: 82.87% / [[270, 92], [67, 499]], * Val accuracy / confusion: 73.73% / [[144, 86], [69, 291]] ------------------------------ Epoch 392 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.420760 - Iter 028 / 029, Loss: 0.286159 * Train accuracy / confusion: 82.33% / [[267, 96], [68, 497]], * Val accuracy / confusion: 73.73% / [[133, 97], [58, 302]] ------------------------------ Epoch 393 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.374815 - Iter 028 / 029, Loss: 0.334971 * Train accuracy / confusion: 82.54% / [[264, 97], [65, 502]], * Val accuracy / confusion: 73.73% / [[137, 93], [62, 298]] ------------------------------ Epoch 394 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.373435 - Iter 028 / 029, Loss: 0.390772 * Train accuracy / confusion: 82.65% / [[265, 97], [64, 502]], * Val accuracy / confusion: 73.56% / [[136, 94], [62, 298]] ------------------------------ Epoch 395 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.372248 - Iter 028 / 029, Loss: 0.345174 * Train accuracy / confusion: 83.41% / [[279, 84], [70, 495]], * Val accuracy / confusion: 73.22% / [[149, 81], [77, 283]] ------------------------------ Epoch 396 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.463446 - Iter 028 / 029, Loss: 0.247772 * Train accuracy / confusion: 81.25% / [[262, 100], [74, 492]], * Val accuracy / confusion: 73.05% / [[138, 92], [67, 293]] ------------------------------ Epoch 397 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.306840 - Iter 028 / 029, Loss: 0.263249 * Train accuracy / confusion: 81.90% / [[262, 101], [67, 498]], * Val accuracy / confusion: 73.05% / [[143, 87], [72, 288]] ------------------------------ Epoch 398 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.325769 - Iter 028 / 029, Loss: 0.322970 * Train accuracy / confusion: 82.54% / [[261, 99], [63, 505]], * Val accuracy / confusion: 73.39% / [[142, 88], [69, 291]] ------------------------------ Epoch 399 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.295122 - Iter 028 / 029, Loss: 0.399755 * Train accuracy / confusion: 84.16% / [[271, 89], [58, 510]], * Val accuracy / confusion: 75.76% / [[147, 83], [60, 300]] ------------------------------ Epoch 400 / 500, Learning rate: 9.56e-04 ------------------------------ - Iter 014 / 029, Loss: 0.282597 - Iter 028 / 029, Loss: 0.404008 * Train accuracy / confusion: 81.47% / [[260, 104], [68, 496]], * Val accuracy / confusion: 72.03% / [[138, 92], [73, 287]] ------------------------------ Epoch 401 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.529050 - Iter 028 / 029, Loss: 0.312400 * Train accuracy / confusion: 82.00% / [[269, 91], [76, 492]], * Val accuracy / confusion: 75.42% / [[133, 97], [48, 312]] ------------------------------ Epoch 402 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.393908 - Iter 028 / 029, Loss: 0.462052 * Train accuracy / confusion: 82.65% / [[265, 95], [66, 502]], * Val accuracy / confusion: 76.44% / [[137, 93], [46, 314]] ------------------------------ Epoch 403 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.192966 - Iter 028 / 029, Loss: 0.648361 * Train accuracy / confusion: 82.87% / [[279, 83], [76, 490]], * Val accuracy / confusion: 73.90% / [[147, 83], [71, 289]] ------------------------------ Epoch 404 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.268693 - Iter 028 / 029, Loss: 0.319013 * Train accuracy / confusion: 82.44% / [[266, 93], [70, 499]], * Val accuracy / confusion: 73.22% / [[139, 91], [67, 293]] ------------------------------ Epoch 405 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.464756 - Iter 028 / 029, Loss: 0.520996 * Train accuracy / confusion: 82.76% / [[272, 89], [71, 496]], * Val accuracy / confusion: 73.73% / [[143, 87], [68, 292]] ------------------------------ Epoch 406 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.424488 - Iter 028 / 029, Loss: 0.532073 * Train accuracy / confusion: 81.36% / [[265, 98], [75, 490]], * Val accuracy / confusion: 73.39% / [[137, 93], [64, 296]] ------------------------------ Epoch 407 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.288462 - Iter 028 / 029, Loss: 0.316404 * Train accuracy / confusion: 82.97% / [[271, 88], [70, 499]], * Val accuracy / confusion: 72.37% / [[133, 97], [66, 294]] ------------------------------ Epoch 408 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.311412 - Iter 028 / 029, Loss: 0.417052 * Train accuracy / confusion: 83.30% / [[274, 88], [67, 499]], * Val accuracy / confusion: 73.73% / [[142, 88], [67, 293]] ------------------------------ Epoch 409 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.300107 - Iter 028 / 029, Loss: 0.340573 * Train accuracy / confusion: 83.41% / [[272, 92], [62, 502]], * Val accuracy / confusion: 75.59% / [[143, 87], [57, 303]] ------------------------------ Epoch 410 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.363429 - Iter 028 / 029, Loss: 0.372153 * Train accuracy / confusion: 81.68% / [[262, 101], [69, 496]], * Val accuracy / confusion: 73.05% / [[139, 91], [68, 292]] ------------------------------ Epoch 411 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.369273 - Iter 028 / 029, Loss: 0.360471 * Train accuracy / confusion: 82.87% / [[270, 93], [66, 499]], * Val accuracy / confusion: 74.07% / [[149, 81], [72, 288]] ------------------------------ Epoch 412 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.305896 - Iter 028 / 029, Loss: 0.384959 * Train accuracy / confusion: 81.79% / [[251, 109], [60, 508]], * Val accuracy / confusion: 72.20% / [[133, 97], [67, 293]] ------------------------------ Epoch 413 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.389282 - Iter 028 / 029, Loss: 0.329815 * Train accuracy / confusion: 83.30% / [[275, 87], [68, 498]], * Val accuracy / confusion: 76.27% / [[141, 89], [51, 309]] ------------------------------ Epoch 414 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.279755 - Iter 028 / 029, Loss: 0.380743 * Train accuracy / confusion: 81.47% / [[260, 102], [70, 496]], * Val accuracy / confusion: 76.27% / [[145, 85], [55, 305]] ------------------------------ Epoch 415 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.453851 - Iter 028 / 029, Loss: 0.479612 * Train accuracy / confusion: 82.97% / [[266, 93], [65, 504]], * Val accuracy / confusion: 73.90% / [[139, 91], [63, 297]] ------------------------------ Epoch 416 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.406931 - Iter 028 / 029, Loss: 0.427120 * Train accuracy / confusion: 80.93% / [[263, 96], [81, 488]], * Val accuracy / confusion: 74.07% / [[144, 86], [67, 293]] ------------------------------ Epoch 417 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.233580 - Iter 028 / 029, Loss: 0.606566 * Train accuracy / confusion: 84.27% / [[275, 82], [64, 507]], * Val accuracy / confusion: 74.07% / [[141, 89], [64, 296]] ------------------------------ Epoch 418 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.381772 - Iter 028 / 029, Loss: 0.641457 * Train accuracy / confusion: 81.36% / [[263, 101], [72, 492]], * Val accuracy / confusion: 74.58% / [[134, 96], [54, 306]] ------------------------------ Epoch 419 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.193346 - Iter 028 / 029, Loss: 0.481310 * Train accuracy / confusion: 82.65% / [[261, 103], [58, 506]], * Val accuracy / confusion: 73.05% / [[132, 98], [61, 299]] ------------------------------ Epoch 420 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.406663 - Iter 028 / 029, Loss: 0.496289 * Train accuracy / confusion: 82.00% / [[269, 92], [75, 492]], * Val accuracy / confusion: 75.08% / [[148, 82], [65, 295]] ------------------------------ Epoch 421 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.275003 - Iter 028 / 029, Loss: 0.246395 * Train accuracy / confusion: 81.25% / [[260, 100], [74, 494]], * Val accuracy / confusion: 74.24% / [[139, 91], [61, 299]] ------------------------------ Epoch 422 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.344546 - Iter 028 / 029, Loss: 0.408716 * Train accuracy / confusion: 82.65% / [[264, 95], [66, 503]], * Val accuracy / confusion: 73.22% / [[135, 95], [63, 297]] ------------------------------ Epoch 423 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.397077 - Iter 028 / 029, Loss: 0.451938 * Train accuracy / confusion: 81.90% / [[265, 99], [69, 495]], * Val accuracy / confusion: 75.76% / [[143, 87], [56, 304]] ------------------------------ Epoch 424 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.195653 - Iter 028 / 029, Loss: 0.373730 * Train accuracy / confusion: 81.68% / [[263, 97], [73, 495]], * Val accuracy / confusion: 74.58% / [[144, 86], [64, 296]] ------------------------------ Epoch 425 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.360116 - Iter 028 / 029, Loss: 0.219056 * Train accuracy / confusion: 82.11% / [[266, 99], [67, 496]], * Val accuracy / confusion: 74.24% / [[139, 91], [61, 299]] ------------------------------ Epoch 426 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.537256 - Iter 028 / 029, Loss: 0.444198 * Train accuracy / confusion: 82.54% / [[265, 97], [65, 501]], * Val accuracy / confusion: 73.90% / [[139, 91], [63, 297]] ------------------------------ Epoch 427 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.319713 - Iter 028 / 029, Loss: 0.362802 * Train accuracy / confusion: 83.51% / [[271, 92], [61, 504]], * Val accuracy / confusion: 74.24% / [[139, 91], [61, 299]] ------------------------------ Epoch 428 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.467483 - Iter 028 / 029, Loss: 0.608673 * Train accuracy / confusion: 81.47% / [[263, 96], [76, 493]], * Val accuracy / confusion: 72.71% / [[137, 93], [68, 292]] ------------------------------ Epoch 429 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.257080 - Iter 028 / 029, Loss: 0.317332 * Train accuracy / confusion: 84.70% / [[274, 88], [54, 512]], * Val accuracy / confusion: 74.92% / [[149, 81], [67, 293]] ------------------------------ Epoch 430 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.332734 - Iter 028 / 029, Loss: 0.432906 * Train accuracy / confusion: 84.16% / [[277, 87], [60, 504]], * Val accuracy / confusion: 74.24% / [[140, 90], [62, 298]] ------------------------------ Epoch 431 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.390977 - Iter 028 / 029, Loss: 0.458553 * Train accuracy / confusion: 83.08% / [[271, 91], [66, 500]], * Val accuracy / confusion: 75.76% / [[141, 89], [54, 306]] ------------------------------ Epoch 432 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.384990 - Iter 028 / 029, Loss: 0.165437 * Train accuracy / confusion: 82.00% / [[264, 96], [71, 497]], * Val accuracy / confusion: 75.25% / [[144, 86], [60, 300]] ------------------------------ Epoch 433 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.623936 - Iter 028 / 029, Loss: 0.378977 * Train accuracy / confusion: 81.90% / [[257, 106], [62, 503]], * Val accuracy / confusion: 76.10% / [[146, 84], [57, 303]] ------------------------------ Epoch 434 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.388748 - Iter 028 / 029, Loss: 0.598940 * Train accuracy / confusion: 83.94% / [[267, 94], [55, 512]], * Val accuracy / confusion: 72.71% / [[129, 101], [60, 300]] ------------------------------ Epoch 435 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.298271 - Iter 028 / 029, Loss: 0.218553 * Train accuracy / confusion: 82.97% / [[260, 99], [59, 510]], * Val accuracy / confusion: 73.56% / [[138, 92], [64, 296]] ------------------------------ Epoch 436 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.608496 - Iter 028 / 029, Loss: 0.350094 * Train accuracy / confusion: 82.65% / [[268, 96], [65, 499]], * Val accuracy / confusion: 72.37% / [[127, 103], [60, 300]] ------------------------------ Epoch 437 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.440001 - Iter 028 / 029, Loss: 0.357553 * Train accuracy / confusion: 81.57% / [[255, 103], [68, 502]], * Val accuracy / confusion: 74.58% / [[144, 86], [64, 296]] ------------------------------ Epoch 438 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.350488 - Iter 028 / 029, Loss: 0.349315 * Train accuracy / confusion: 82.44% / [[264, 97], [66, 501]], * Val accuracy / confusion: 74.92% / [[140, 90], [58, 302]] ------------------------------ Epoch 439 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.503910 - Iter 028 / 029, Loss: 0.437923 * Train accuracy / confusion: 82.76% / [[273, 91], [69, 495]], * Val accuracy / confusion: 74.07% / [[138, 92], [61, 299]] ------------------------------ Epoch 440 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.534366 - Iter 028 / 029, Loss: 0.426392 * Train accuracy / confusion: 81.68% / [[268, 97], [73, 490]], * Val accuracy / confusion: 73.90% / [[143, 87], [67, 293]] ------------------------------ Epoch 441 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.464827 - Iter 028 / 029, Loss: 0.414302 * Train accuracy / confusion: 82.44% / [[262, 101], [62, 503]], * Val accuracy / confusion: 75.76% / [[132, 98], [45, 315]] ------------------------------ Epoch 442 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.432141 - Iter 028 / 029, Loss: 0.513496 * Train accuracy / confusion: 83.84% / [[278, 89], [61, 500]], * Val accuracy / confusion: 74.24% / [[143, 87], [65, 295]] ------------------------------ Epoch 443 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.510019 - Iter 028 / 029, Loss: 0.261024 * Train accuracy / confusion: 82.11% / [[262, 100], [66, 500]], * Val accuracy / confusion: 73.56% / [[141, 89], [67, 293]] ------------------------------ Epoch 444 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.422362 - Iter 028 / 029, Loss: 0.408540 * Train accuracy / confusion: 84.59% / [[268, 91], [52, 517]], * Val accuracy / confusion: 76.10% / [[148, 82], [59, 301]] ------------------------------ Epoch 445 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.265767 - Iter 028 / 029, Loss: 0.447463 * Train accuracy / confusion: 83.19% / [[271, 90], [66, 501]], * Val accuracy / confusion: 74.07% / [[140, 90], [63, 297]] ------------------------------ Epoch 446 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.333814 - Iter 028 / 029, Loss: 0.451772 * Train accuracy / confusion: 83.19% / [[274, 86], [70, 498]], * Val accuracy / confusion: 73.90% / [[139, 91], [63, 297]] ------------------------------ Epoch 447 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.394690 - Iter 028 / 029, Loss: 0.338153 * Train accuracy / confusion: 82.44% / [[270, 92], [71, 495]], * Val accuracy / confusion: 74.07% / [[139, 91], [62, 298]] ------------------------------ Epoch 448 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.440739 - Iter 028 / 029, Loss: 0.238788 * Train accuracy / confusion: 81.79% / [[263, 99], [70, 496]], * Val accuracy / confusion: 75.08% / [[141, 89], [58, 302]] ------------------------------ Epoch 449 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.407008 - Iter 028 / 029, Loss: 0.354595 * Train accuracy / confusion: 83.41% / [[270, 92], [62, 504]], * Val accuracy / confusion: 72.54% / [[141, 89], [73, 287]] ------------------------------ Epoch 450 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.263445 - Iter 028 / 029, Loss: 0.402553 * Train accuracy / confusion: 83.51% / [[276, 85], [68, 499]], * Val accuracy / confusion: 71.86% / [[135, 95], [71, 289]] ------------------------------ Epoch 451 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.225311 - Iter 028 / 029, Loss: 0.607630 * Train accuracy / confusion: 82.97% / [[269, 92], [66, 501]], * Val accuracy / confusion: 72.20% / [[139, 91], [73, 287]] ------------------------------ Epoch 452 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.247698 - Iter 028 / 029, Loss: 0.306980 * Train accuracy / confusion: 82.22% / [[266, 98], [67, 497]], * Val accuracy / confusion: 75.25% / [[152, 78], [68, 292]] ------------------------------ Epoch 453 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.330668 - Iter 028 / 029, Loss: 0.380760 * Train accuracy / confusion: 82.22% / [[270, 93], [72, 493]], * Val accuracy / confusion: 73.73% / [[142, 88], [67, 293]] ------------------------------ Epoch 454 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.382459 - Iter 028 / 029, Loss: 0.556243 * Train accuracy / confusion: 82.97% / [[273, 89], [69, 497]], * Val accuracy / confusion: 73.73% / [[145, 85], [70, 290]] ------------------------------ Epoch 455 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.330673 - Iter 028 / 029, Loss: 0.260246 * Train accuracy / confusion: 83.51% / [[271, 89], [64, 504]], * Val accuracy / confusion: 74.24% / [[148, 82], [70, 290]] ------------------------------ Epoch 456 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.283479 - Iter 028 / 029, Loss: 0.413986 * Train accuracy / confusion: 83.30% / [[276, 90], [65, 497]], * Val accuracy / confusion: 74.41% / [[146, 84], [67, 293]] ------------------------------ Epoch 457 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.588723 - Iter 028 / 029, Loss: 0.473537 * Train accuracy / confusion: 83.84% / [[275, 87], [63, 503]], * Val accuracy / confusion: 75.25% / [[152, 78], [68, 292]] ------------------------------ Epoch 458 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.500765 - Iter 028 / 029, Loss: 0.282313 * Train accuracy / confusion: 81.57% / [[263, 96], [75, 494]], * Val accuracy / confusion: 75.08% / [[144, 86], [61, 299]] ------------------------------ Epoch 459 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.363853 - Iter 028 / 029, Loss: 0.335262 * Train accuracy / confusion: 82.76% / [[269, 94], [66, 499]], * Val accuracy / confusion: 73.56% / [[133, 97], [59, 301]] ------------------------------ Epoch 460 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.474168 - Iter 028 / 029, Loss: 0.386715 * Train accuracy / confusion: 81.57% / [[257, 105], [66, 500]], * Val accuracy / confusion: 75.08% / [[155, 75], [72, 288]] ------------------------------ Epoch 461 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.333104 - Iter 028 / 029, Loss: 0.396741 * Train accuracy / confusion: 82.00% / [[261, 100], [67, 500]], * Val accuracy / confusion: 73.22% / [[138, 92], [66, 294]] ------------------------------ Epoch 462 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.479610 - Iter 028 / 029, Loss: 0.314411 * Train accuracy / confusion: 81.68% / [[260, 99], [71, 498]], * Val accuracy / confusion: 73.56% / [[144, 86], [70, 290]] ------------------------------ Epoch 463 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.608063 - Iter 028 / 029, Loss: 0.291349 * Train accuracy / confusion: 82.44% / [[262, 96], [67, 503]], * Val accuracy / confusion: 73.56% / [[144, 86], [70, 290]] ------------------------------ Epoch 464 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.551078 - Iter 028 / 029, Loss: 0.335876 * Train accuracy / confusion: 81.03% / [[259, 104], [72, 493]], * Val accuracy / confusion: 74.75% / [[145, 85], [64, 296]] ------------------------------ Epoch 465 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.411474 - Iter 028 / 029, Loss: 0.450492 * Train accuracy / confusion: 82.87% / [[276, 90], [69, 493]], * Val accuracy / confusion: 72.88% / [[130, 100], [60, 300]] ------------------------------ Epoch 466 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.390342 - Iter 028 / 029, Loss: 0.394533 * Train accuracy / confusion: 80.82% / [[262, 102], [76, 488]], * Val accuracy / confusion: 76.44% / [[141, 89], [50, 310]] ------------------------------ Epoch 467 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.457486 - Iter 028 / 029, Loss: 0.350249 * Train accuracy / confusion: 83.41% / [[275, 89], [65, 499]], * Val accuracy / confusion: 73.22% / [[140, 90], [68, 292]] ------------------------------ Epoch 468 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.345736 - Iter 028 / 029, Loss: 0.431703 * Train accuracy / confusion: 83.73% / [[270, 94], [57, 507]], * Val accuracy / confusion: 74.58% / [[132, 98], [52, 308]] ------------------------------ Epoch 469 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.364855 - Iter 028 / 029, Loss: 0.674126 * Train accuracy / confusion: 82.87% / [[271, 94], [65, 498]], * Val accuracy / confusion: 74.58% / [[141, 89], [61, 299]] ------------------------------ Epoch 470 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.391441 - Iter 028 / 029, Loss: 0.281189 * Train accuracy / confusion: 83.73% / [[276, 89], [62, 501]], * Val accuracy / confusion: 73.39% / [[137, 93], [64, 296]] ------------------------------ Epoch 471 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.520606 - Iter 028 / 029, Loss: 0.531157 * Train accuracy / confusion: 82.33% / [[267, 95], [69, 497]], * Val accuracy / confusion: 74.75% / [[135, 95], [54, 306]] ------------------------------ Epoch 472 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.401080 - Iter 028 / 029, Loss: 0.381243 * Train accuracy / confusion: 82.44% / [[267, 95], [68, 498]], * Val accuracy / confusion: 74.58% / [[147, 83], [67, 293]] ------------------------------ Epoch 473 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.399257 - Iter 028 / 029, Loss: 0.485151 * Train accuracy / confusion: 82.44% / [[272, 90], [73, 493]], * Val accuracy / confusion: 74.75% / [[142, 88], [61, 299]] ------------------------------ Epoch 474 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.538056 - Iter 028 / 029, Loss: 0.227767 * Train accuracy / confusion: 83.30% / [[273, 89], [66, 500]], * Val accuracy / confusion: 73.22% / [[144, 86], [72, 288]] ------------------------------ Epoch 475 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.376695 - Iter 028 / 029, Loss: 0.246048 * Train accuracy / confusion: 82.22% / [[270, 90], [75, 493]], * Val accuracy / confusion: 74.41% / [[138, 92], [59, 301]] ------------------------------ Epoch 476 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.633906 - Iter 028 / 029, Loss: 0.504001 * Train accuracy / confusion: 81.14% / [[255, 105], [70, 498]], * Val accuracy / confusion: 73.39% / [[142, 88], [69, 291]] ------------------------------ Epoch 477 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.304998 - Iter 028 / 029, Loss: 0.290524 * Train accuracy / confusion: 82.11% / [[274, 92], [74, 488]], * Val accuracy / confusion: 72.37% / [[133, 97], [66, 294]] ------------------------------ Epoch 478 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.538577 - Iter 028 / 029, Loss: 0.652294 * Train accuracy / confusion: 83.84% / [[279, 86], [64, 499]], * Val accuracy / confusion: 73.56% / [[136, 94], [62, 298]] ------------------------------ Epoch 479 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.240559 - Iter 028 / 029, Loss: 0.396842 * Train accuracy / confusion: 81.47% / [[259, 103], [69, 497]], * Val accuracy / confusion: 74.58% / [[145, 85], [65, 295]] ------------------------------ Epoch 480 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.375484 - Iter 028 / 029, Loss: 0.284796 * Train accuracy / confusion: 82.65% / [[266, 93], [68, 501]], * Val accuracy / confusion: 74.41% / [[142, 88], [63, 297]] ------------------------------ Epoch 481 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.341561 - Iter 028 / 029, Loss: 0.460577 * Train accuracy / confusion: 82.87% / [[267, 96], [63, 502]], * Val accuracy / confusion: 75.76% / [[144, 86], [57, 303]] ------------------------------ Epoch 482 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.331049 - Iter 028 / 029, Loss: 0.426366 * Train accuracy / confusion: 84.16% / [[269, 93], [54, 512]], * Val accuracy / confusion: 75.08% / [[140, 90], [57, 303]] ------------------------------ Epoch 483 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.354877 - Iter 028 / 029, Loss: 0.438725 * Train accuracy / confusion: 83.51% / [[271, 92], [61, 504]], * Val accuracy / confusion: 72.88% / [[135, 95], [65, 295]] ------------------------------ Epoch 484 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.314259 - Iter 028 / 029, Loss: 0.283377 * Train accuracy / confusion: 84.38% / [[274, 85], [60, 509]], * Val accuracy / confusion: 74.24% / [[141, 89], [63, 297]] ------------------------------ Epoch 485 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.253127 - Iter 028 / 029, Loss: 0.519521 * Train accuracy / confusion: 81.90% / [[265, 98], [70, 495]], * Val accuracy / confusion: 71.19% / [[127, 103], [67, 293]] ------------------------------ Epoch 486 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.333658 - Iter 028 / 029, Loss: 0.275161 * Train accuracy / confusion: 82.00% / [[265, 97], [70, 496]], * Val accuracy / confusion: 73.56% / [[139, 91], [65, 295]] ------------------------------ Epoch 487 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.434797 - Iter 028 / 029, Loss: 0.553604 * Train accuracy / confusion: 85.88% / [[283, 79], [52, 514]], * Val accuracy / confusion: 75.08% / [[146, 84], [63, 297]] ------------------------------ Epoch 488 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.305505 - Iter 028 / 029, Loss: 0.356626 * Train accuracy / confusion: 83.08% / [[275, 83], [74, 496]], * Val accuracy / confusion: 74.58% / [[146, 84], [66, 294]] ------------------------------ Epoch 489 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.248035 - Iter 028 / 029, Loss: 0.578284 * Train accuracy / confusion: 82.44% / [[266, 99], [64, 499]], * Val accuracy / confusion: 73.22% / [[146, 84], [74, 286]] ------------------------------ Epoch 490 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.358779 - Iter 028 / 029, Loss: 0.498673 * Train accuracy / confusion: 81.03% / [[260, 103], [73, 492]], * Val accuracy / confusion: 75.76% / [[145, 85], [58, 302]] ------------------------------ Epoch 491 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.374546 - Iter 028 / 029, Loss: 0.406871 * Train accuracy / confusion: 81.25% / [[264, 98], [76, 490]], * Val accuracy / confusion: 73.90% / [[140, 90], [64, 296]] ------------------------------ Epoch 492 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.596815 - Iter 028 / 029, Loss: 0.476867 * Train accuracy / confusion: 82.00% / [[263, 100], [67, 498]], * Val accuracy / confusion: 73.39% / [[136, 94], [63, 297]] ------------------------------ Epoch 493 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.317820 - Iter 028 / 029, Loss: 0.326885 * Train accuracy / confusion: 83.19% / [[267, 94], [62, 505]], * Val accuracy / confusion: 73.73% / [[141, 89], [66, 294]] ------------------------------ Epoch 494 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.314305 - Iter 028 / 029, Loss: 0.354487 * Train accuracy / confusion: 83.19% / [[268, 96], [60, 504]], * Val accuracy / confusion: 74.58% / [[140, 90], [60, 300]] ------------------------------ Epoch 495 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.349116 - Iter 028 / 029, Loss: 0.557052 * Train accuracy / confusion: 82.33% / [[266, 94], [70, 498]], * Val accuracy / confusion: 74.58% / [[144, 86], [64, 296]] ------------------------------ Epoch 496 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.332235 - Iter 028 / 029, Loss: 0.406870 * Train accuracy / confusion: 84.16% / [[276, 86], [61, 505]], * Val accuracy / confusion: 72.54% / [[134, 96], [66, 294]] ------------------------------ Epoch 497 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.180964 - Iter 028 / 029, Loss: 0.313908 * Train accuracy / confusion: 82.97% / [[267, 96], [62, 503]], * Val accuracy / confusion: 74.58% / [[137, 93], [57, 303]] ------------------------------ Epoch 498 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.296993 - Iter 028 / 029, Loss: 0.334516 * Train accuracy / confusion: 82.65% / [[274, 90], [71, 493]], * Val accuracy / confusion: 75.42% / [[148, 82], [63, 297]] ------------------------------ Epoch 499 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.477398 - Iter 028 / 029, Loss: 0.461907 * Train accuracy / confusion: 82.87% / [[264, 99], [60, 505]], * Val accuracy / confusion: 72.37% / [[138, 92], [71, 289]] ------------------------------ Epoch 500 / 500, Learning rate: 9.56e-05 ------------------------------ - Iter 014 / 029, Loss: 0.359549 - Iter 028 / 029, Loss: 0.332107 * Train accuracy / confusion: 83.94% / [[272, 92], [57, 507]], * Val accuracy / confusion: 74.41% / [[143, 87], [64, 296]] **************************************** Training Ends ****************************************
- Test accuracy (last model): 72.00% - Confusion matrix (last model): [[ 913 497] [ 511 1679]]
- Test accuracy (best model): 72.47% - Confusion matrix (best model): [[ 934 476] [ 515 1675]]
# checkpoint save path
if save_checkpoint:
os.makedirs('checkpoint/', exist_ok=True)
today = datetime.date.today()
torch.save(best_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_TinyCNN_best')
torch.save(last_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_TinyCNN_last')
print('- Debug table:')
pprint.pp(last_test_debug, indent=2, width=100)
- Debug table:
{ '01183': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01303198_020317'},
'00697': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00983533_290618'},
'00825': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01129445_130220'},
'00504': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00813343_041218'},
'00192': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00608961_131118'},
'00134': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00446328_171116'},
'00741': {'GT': 0, 'Acc': ' 46.67%', 'Pred': [14, 16], 'edfname': '01025734_280715'},
'00206': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00616193_090218'},
'01231': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01334787_211117'},
'00793': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01086373_020615'},
'01045': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01235281_191015'},
'00407': {'GT': 1, 'Acc': ' 36.67%', 'Pred': [19, 11], 'edfname': '00740694_110315'},
'00669': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '00957862_230317'},
'00843': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01135545_230715'},
'00029': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00164098_180919'},
'00299': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00671212_160819'},
'00702': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00985987_180518'},
'01069': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01243158_301115'},
'00913': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01151967_160414'},
'01307': {'GT': 0, 'Acc': ' 3.33%', 'Pred': [1, 29], 'edfname': '01376302_060718'},
'00638': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00941649_111218'},
'00286': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '00663561_030414'},
'00954': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '01178797_240914'},
'00587': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00894185_250817'},
'00542': {'GT': 1, 'Acc': ' 76.67%', 'Pred': [7, 23], 'edfname': '00852650_170818'},
'00996': {'GT': 1, 'Acc': ' 60.00%', 'Pred': [12, 18], 'edfname': '01204692_120315'},
'00403': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00739162_011215'},
'00408': {'GT': 0, 'Acc': ' 3.33%', 'Pred': [1, 29], 'edfname': '00740750_110315'},
'00078': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00324958_271118'},
'00277': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00657017_281218'},
'00671': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00958455_200917'},
'01066': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01242983_071215'},
'00965': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '01186214'},
'01125': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01276737_300616'},
'00227': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00626957_071217'},
'00531': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '00840844_250119'},
'00088': {'GT': 1, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '00344923_021116'},
'00267': {'GT': 1, 'Acc': ' 80.00%', 'Pred': [6, 24], 'edfname': '00650465_160318'},
'00069': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00307906_230617'},
'00365': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00712852_060418'},
'00991': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01203444_090819'},
'00815': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01125477_030918'},
'01351': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01409497_111219'},
'00065': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00293228_070918'},
'00952': {'GT': 1, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '01178672_300518'},
'00124': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00418981_060116'},
'00854': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01138301_230114'},
'00472': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00784418_201016'},
'01258': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01348039_181017'},
'01375': {'GT': 1, 'Acc': ' 63.33%', 'Pred': [11, 19], 'edfname': '01429374_230519'},
'00885': {'GT': 0, 'Acc': ' 40.00%', 'Pred': [12, 18], 'edfname': '01142810_180214'},
'00917': {'GT': 0, 'Acc': ' 13.33%', 'Pred': [4, 26], 'edfname': '01154159_230414'},
'00938': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '01161826_050916'},
'00881': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01141790_190214'},
'00096': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00369252_131216'},
'01075': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01250004_260116'},
'01165': {'GT': 0, 'Acc': ' 40.00%', 'Pred': [12, 18], 'edfname': '01296533_281116'},
'01067': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01242984_211215'},
'00828': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01131959_310118'},
'01337': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01400560_160419'},
'00383': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00723110_240419'},
'00900': {'GT': 0, 'Acc': ' 26.67%', 'Pred': [8, 22], 'edfname': '01147100'},
'01336': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01398060_050918'},
'01115': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01271298_270319'},
'00667': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00956561_241116'},
'00439': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00760780_141118'},
'00369': {'GT': 1, 'Acc': ' 10.00%', 'Pred': [27, 3], 'edfname': '00715828_111016'},
'00955': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01178888_161117'},
'00300': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00671379_290617'},
'01196': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01307883_100217'},
'00923': {'GT': 0, 'Acc': ' 63.33%', 'Pred': [19, 11], 'edfname': '01155730_070514'},
'00058': {'GT': 0, 'Acc': ' 20.00%', 'Pred': [6, 24], 'edfname': '00285244_020414'},
'00584': {'GT': 1, 'Acc': ' 16.67%', 'Pred': [25, 5], 'edfname': '00891889_060717'},
'00749': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01027623_260916'},
'01334': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01396872_021018'},
'00588': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00895530_090616'},
'00679': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00963069_150618'},
'00385': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00723232_270318'},
'00018': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00128526_180817'},
'01281': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '01358607_280918'},
'00651': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00951808_251116'},
'01253': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01344212_240817'},
'01035': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01231654_260417'},
'00551': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00865039_170816'},
'00870': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01139947_120214'},
'00578': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00888613_080618'},
'00730': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01011922_270815'},
'00516': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00823206_130514'},
'01330': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '01392885_240718'},
'00944': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01168853_070316'},
'00125': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '00418981_090316'},
'00508': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00817022_010415'},
'01317': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01381606_160518'},
'00608': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '00907971_030217'},
'00471': {'GT': 1, 'Acc': ' 76.67%', 'Pred': [7, 23], 'edfname': '00784417_100315'},
'00821': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01128393_300715'},
'00122': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00416942_190516'},
'01007': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01211467_070415'},
'01247': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01339759_310717'},
'00173': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00601028_290618'},
'01026': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01225123_050815'},
'01018': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01216443_240518'},
'00418': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '00745209_220916'},
'01206': {'GT': 1, 'Acc': ' 3.33%', 'Pred': [29, 1], 'edfname': '01314786_200317'},
'01215': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01321744_130417'},
'01105': {'GT': 0, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '01266696_110516'},
'00598': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '00899964_110414'},
'00851': {'GT': 0, 'Acc': ' 10.00%', 'Pred': [3, 27], 'edfname': '01138297_230114'},
'01138': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '01281605_070716'},
'00079': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00325929_170119'},
'00245': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00637371_050917'},
'00591': {'GT': 0, 'Acc': ' 63.33%', 'Pred': [19, 11], 'edfname': '00896386_240914'},
'00329': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '00685248_150414'},
'00272': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00651389_281016'},
'00176': {'GT': 0, 'Acc': ' 56.67%', 'Pred': [17, 13], 'edfname': '00602435_270217'},
'00807': {'GT': 1, 'Acc': ' 13.33%', 'Pred': [26, 4], 'edfname': '01112291_231115'},
'00271': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00651252_140618'},
'00712': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00988278_210915'},
'00974': {'GT': 1, 'Acc': ' 36.67%', 'Pred': [19, 11], 'edfname': '01193508_171214'},
'01163': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01296342_141116'}}
class M5(nn.Module):
def __init__(self, n_input=20, n_output=3, stride=4, n_channel=256,
use_age=True, final_pool='average'):
super().__init__()
if final_pool not in {'average', 'max'}:
raise ValueError("final_pool must be set to one of ['average', 'max']")
self.use_age = use_age
self.conv1 = nn.Conv1d(n_input, n_channel, kernel_size=41, stride=2)
self.bn1 = nn.BatchNorm1d(n_channel)
self.pool1 = nn.MaxPool1d(2)
self.conv2 = nn.Conv1d(n_channel, n_channel, kernel_size=11)
self.bn2 = nn.BatchNorm1d(n_channel)
self.pool2 = nn.MaxPool1d(2)
self.conv3 = nn.Conv1d(n_channel, 2 * n_channel, kernel_size=11)
self.bn3 = nn.BatchNorm1d(2 * n_channel)
self.pool3 = nn.MaxPool1d(2)
self.conv4 = nn.Conv1d(2 * n_channel, 2 * n_channel, kernel_size=11)
self.bn4 = nn.BatchNorm1d(2 * n_channel)
self.pool4 = nn.MaxPool1d(2)
self.conv5 = nn.Conv1d(2 * n_channel, 2 * n_channel, kernel_size=11)
self.bn5 = nn.BatchNorm1d(2 * n_channel)
self.pool5 = nn.MaxPool1d(2)
if final_pool == 'average':
self.final_pool = nn.AdaptiveAvgPool1d(1)
elif final_pool == 'max':
self.final_pool = nn.AdaptiveMaxPool1d(1)
if self.use_age:
self.fc1 = nn.Linear(2 * n_channel + 1, 2 * n_channel)
else:
self.fc1 = nn.Linear(2 * n_channel, 2 * n_channel)
self.dropout = nn.Dropout(p=0.3)
self.bnfc1 = nn.BatchNorm1d(2 * n_channel)
self.fc2 = nn.Linear(2 * n_channel, n_output)
def reset_weights(self):
for m in self.modules():
if hasattr(m, 'reset_parameters'):
m.reset_parameters()
def forward(self, x, age, print_shape=False):
# conv-bn-relu-pool
x = self.conv1(x)
x = F.relu(self.bn1(x))
x = self.pool1(x)
x = self.conv2(x)
x = F.relu(self.bn2(x))
x = self.pool2(x)
x = self.conv3(x)
x = F.relu(self.bn3(x))
x = self.pool3(x)
x = self.conv4(x)
x = F.relu(self.bn4(x))
x = self.pool4(x)
x = self.conv5(x)
x = F.relu(self.bn5(x))
x = self.pool5(x)
if print_shape:
print('Shape right before squeezing:', x.shape)
x = self.final_pool(x).squeeze()
if self.use_age:
x = torch.cat((x, age.reshape(-1, 1)), dim=1)
# fc-bn-dropout-relu-fc
x = self.fc1(x)
x = self.bnfc1(x)
x = self.dropout(x)
x = F.relu(x)
x = self.fc2(x)
return x
# return F.log_softmax(x, dim=1)
model = M5(n_input=train_dataset[0]['signal'].shape[0],
n_output=2,
use_age=True,
final_pool='max')
model = model.to(device, dtype=torch.float32)
print(model)
print()
# tensorboard visualization
visualize_network_tensorboard(model, 'M5-like')
# number of parameters
n = count_parameters(model)
print(f'The Number of parameters of the model: {n:,}')
M5( (conv1): Conv1d(20, 256, kernel_size=(41,), stride=(2,)) (bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool1): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) (conv2): Conv1d(256, 256, kernel_size=(11,), stride=(1,)) (bn2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool2): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) (conv3): Conv1d(256, 512, kernel_size=(11,), stride=(1,)) (bn3): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool3): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) (conv4): Conv1d(512, 512, kernel_size=(11,), stride=(1,)) (bn4): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool4): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) (conv5): Conv1d(512, 512, kernel_size=(11,), stride=(1,)) (bn5): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool5): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) (final_pool): AdaptiveMaxPool1d(output_size=1) (fc1): Linear(in_features=513, out_features=512, bias=True) (dropout): Dropout(p=0.3, inplace=False) (bnfc1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (fc2): Linear(in_features=512, out_features=2, bias=True) ) Shape right before squeezing: torch.Size([32, 512, 21]) The Number of parameters of the model: 8,411,138
record = learning_rate_search(model,
min_log_lr=-4.5,
max_log_lr=-1.4,
trials=300,
epochs=1)
draw_learning_rate_record(record)
best_log_lr = record[np.argmax(np.array([v for lr, v in record]))][0]
# best_log_lr = -3.5
print('best_log_lr:', best_log_lr)
best_log_lr: -2.7162397010443335
# reduce the learning after [lr_schedule_step] epochs by a factor of 10
n_epoch = 500
lr_schedule_step = 200
log_interval = len(train_loader) // 2
loss_history = []
train_acc_history = []
val_acc_history = []
best_val_acc = 0
model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=10 ** best_log_lr, weight_decay=0.0001)
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=lr_schedule_step, gamma=0.1)
print(f'{"*"*40} Training Starts {"*"*40}')
for epoch in tqdm(range(1, n_epoch + 1)):
print(f'{"-"*30} Epoch {epoch:03d} / {n_epoch:03d}, Learning rate: {optimizer.param_groups[-1]["lr"]:.2e} {"-"*30}')
# train
loss, train_accuracy, train_confusion = train_one_epoch(model, optimizer, log_interval)
loss_history.extend(loss)
train_acc_history.append(train_accuracy)
# validation
val_accuracy, val_confusion = check_val_accuracy(model, repeat=5)
val_acc_history.append(val_accuracy)
if best_val_acc < val_accuracy:
best_val_acc = val_accuracy
best_model_state = deepcopy(model.state_dict())
# learning rate schedule
scheduler.step()
print()
print(f'* Train accuracy / confusion: {train_accuracy:.2f}% / {train_confusion.tolist()}, ')
print(f'* Val accuracy / confusion: {val_accuracy:.2f}% / {val_confusion.tolist()}')
print()
print(f'{"*"*40} Training Ends {"*"*40}')
# draw the training loss plot
draw_loss_plot(loss_history)
draw_accuracy_history(train_acc_history, val_acc_history)
# test the last model
last_model_state = deepcopy(model.state_dict())
last_test_accuracy, last_test_confusion, last_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (last model): {last_test_accuracy:.2f}%')
print('- Confusion matrix (last model):\n', last_test_confusion)
print()
draw_confusion(last_test_confusion)
# test the best model
model.load_state_dict(best_model_state)
best_test_accuracy, best_test_confusion, best_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (best model): {best_test_accuracy:.2f}%')
print('- Confusion matrix (best model):\n', best_test_confusion)
print()
draw_confusion(best_test_confusion)
**************************************** Training Starts ****************************************
------------------------------ Epoch 001 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.685462 - Iter 028 / 029, Loss: 0.678188 * Train accuracy / confusion: 58.51% / [[131, 232], [153, 412]], * Val accuracy / confusion: 55.08% / [[123, 107], [158, 202]] ------------------------------ Epoch 002 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.687887 - Iter 028 / 029, Loss: 0.731904 * Train accuracy / confusion: 59.59% / [[107, 257], [118, 446]], * Val accuracy / confusion: 61.02% / [[79, 151], [79, 281]] ------------------------------ Epoch 003 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.810514 - Iter 028 / 029, Loss: 0.706069 * Train accuracy / confusion: 61.85% / [[103, 261], [93, 471]], * Val accuracy / confusion: 63.22% / [[33, 197], [20, 340]] ------------------------------ Epoch 004 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.703000 - Iter 028 / 029, Loss: 0.671123 * Train accuracy / confusion: 62.93% / [[125, 241], [103, 459]], * Val accuracy / confusion: 61.53% / [[3, 227], [0, 360]] ------------------------------ Epoch 005 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.602015 - Iter 028 / 029, Loss: 0.555473 * Train accuracy / confusion: 66.92% / [[140, 222], [85, 481]], * Val accuracy / confusion: 63.56% / [[20, 210], [5, 355]] ------------------------------ Epoch 006 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.740283 - Iter 028 / 029, Loss: 0.740140 * Train accuracy / confusion: 65.62% / [[148, 214], [105, 461]], * Val accuracy / confusion: 64.58% / [[138, 92], [117, 243]] ------------------------------ Epoch 007 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.587951 - Iter 028 / 029, Loss: 0.714952 * Train accuracy / confusion: 66.81% / [[140, 223], [85, 480]], * Val accuracy / confusion: 60.85% / [[127, 103], [128, 232]] ------------------------------ Epoch 008 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.648321 - Iter 028 / 029, Loss: 0.622020 * Train accuracy / confusion: 67.46% / [[190, 172], [130, 436]], * Val accuracy / confusion: 69.15% / [[71, 159], [23, 337]] ------------------------------ Epoch 009 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.736374 - Iter 028 / 029, Loss: 0.680417 * Train accuracy / confusion: 67.67% / [[182, 181], [119, 446]], * Val accuracy / confusion: 73.39% / [[105, 125], [32, 328]] ------------------------------ Epoch 010 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.562127 - Iter 028 / 029, Loss: 0.434048 * Train accuracy / confusion: 70.58% / [[189, 170], [103, 466]], * Val accuracy / confusion: 67.97% / [[42, 188], [1, 359]] ------------------------------ Epoch 011 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.412661 - Iter 028 / 029, Loss: 0.605394 * Train accuracy / confusion: 71.12% / [[191, 172], [96, 469]], * Val accuracy / confusion: 73.73% / [[168, 62], [93, 267]] ------------------------------ Epoch 012 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.465382 - Iter 028 / 029, Loss: 0.637009 * Train accuracy / confusion: 70.91% / [[196, 166], [104, 462]], * Val accuracy / confusion: 73.05% / [[116, 114], [45, 315]] ------------------------------ Epoch 013 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.634341 - Iter 028 / 029, Loss: 0.600267 * Train accuracy / confusion: 71.55% / [[212, 152], [112, 452]], * Val accuracy / confusion: 71.19% / [[117, 113], [57, 303]] ------------------------------ Epoch 014 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.514843 - Iter 028 / 029, Loss: 0.607926 * Train accuracy / confusion: 66.92% / [[198, 168], [139, 423]], * Val accuracy / confusion: 67.63% / [[48, 182], [9, 351]] ------------------------------ Epoch 015 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.623806 - Iter 028 / 029, Loss: 0.505645 * Train accuracy / confusion: 69.07% / [[185, 174], [113, 456]], * Val accuracy / confusion: 68.31% / [[141, 89], [98, 262]] ------------------------------ Epoch 016 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.554377 - Iter 028 / 029, Loss: 0.416510 * Train accuracy / confusion: 71.12% / [[198, 163], [105, 462]], * Val accuracy / confusion: 71.19% / [[164, 66], [104, 256]] ------------------------------ Epoch 017 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.614937 - Iter 028 / 029, Loss: 0.584349 * Train accuracy / confusion: 70.47% / [[216, 146], [128, 438]], * Val accuracy / confusion: 74.24% / [[125, 105], [47, 313]] ------------------------------ Epoch 018 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.476456 - Iter 028 / 029, Loss: 0.579067 * Train accuracy / confusion: 71.01% / [[196, 167], [102, 463]], * Val accuracy / confusion: 75.42% / [[134, 96], [49, 311]] ------------------------------ Epoch 019 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.700761 - Iter 028 / 029, Loss: 0.607177 * Train accuracy / confusion: 69.94% / [[206, 159], [120, 443]], * Val accuracy / confusion: 72.20% / [[107, 123], [41, 319]] ------------------------------ Epoch 020 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.558230 - Iter 028 / 029, Loss: 0.622491 * Train accuracy / confusion: 70.15% / [[187, 174], [103, 464]], * Val accuracy / confusion: 71.19% / [[118, 112], [58, 302]] ------------------------------ Epoch 021 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.566658 - Iter 028 / 029, Loss: 0.538258 * Train accuracy / confusion: 70.47% / [[185, 172], [102, 469]], * Val accuracy / confusion: 73.39% / [[136, 94], [63, 297]] ------------------------------ Epoch 022 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.533460 - Iter 028 / 029, Loss: 0.590511 * Train accuracy / confusion: 70.26% / [[198, 165], [111, 454]], * Val accuracy / confusion: 76.10% / [[116, 114], [27, 333]] ------------------------------ Epoch 023 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.760657 - Iter 028 / 029, Loss: 0.555490 * Train accuracy / confusion: 71.88% / [[199, 161], [100, 468]], * Val accuracy / confusion: 74.58% / [[153, 77], [73, 287]] ------------------------------ Epoch 024 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.566048 - Iter 028 / 029, Loss: 0.634326 * Train accuracy / confusion: 72.09% / [[212, 150], [109, 457]], * Val accuracy / confusion: 73.05% / [[80, 150], [9, 351]] ------------------------------ Epoch 025 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.704135 - Iter 028 / 029, Loss: 0.709714 * Train accuracy / confusion: 70.37% / [[198, 166], [109, 455]], * Val accuracy / confusion: 76.61% / [[144, 86], [52, 308]] ------------------------------ Epoch 026 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.505385 - Iter 028 / 029, Loss: 0.500971 * Train accuracy / confusion: 72.84% / [[208, 152], [100, 468]], * Val accuracy / confusion: 73.73% / [[120, 110], [45, 315]] ------------------------------ Epoch 027 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.472758 - Iter 028 / 029, Loss: 0.533128 * Train accuracy / confusion: 72.31% / [[210, 153], [104, 461]], * Val accuracy / confusion: 74.24% / [[161, 69], [83, 277]] ------------------------------ Epoch 028 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.540233 - Iter 028 / 029, Loss: 0.604961 * Train accuracy / confusion: 75.43% / [[232, 130], [98, 468]], * Val accuracy / confusion: 74.58% / [[144, 86], [64, 296]] ------------------------------ Epoch 029 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.637030 - Iter 028 / 029, Loss: 0.509313 * Train accuracy / confusion: 72.52% / [[198, 166], [89, 475]], * Val accuracy / confusion: 72.20% / [[100, 130], [34, 326]] ------------------------------ Epoch 030 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.577554 - Iter 028 / 029, Loss: 0.764266 * Train accuracy / confusion: 70.58% / [[188, 172], [101, 467]], * Val accuracy / confusion: 72.54% / [[84, 146], [16, 344]] ------------------------------ Epoch 031 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.735710 - Iter 028 / 029, Loss: 0.620574 * Train accuracy / confusion: 73.60% / [[219, 144], [101, 464]], * Val accuracy / confusion: 71.86% / [[84, 146], [20, 340]] ------------------------------ Epoch 032 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.401889 - Iter 028 / 029, Loss: 0.526930 * Train accuracy / confusion: 73.38% / [[210, 151], [96, 471]], * Val accuracy / confusion: 72.71% / [[155, 75], [86, 274]] ------------------------------ Epoch 033 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.385711 - Iter 028 / 029, Loss: 0.482243 * Train accuracy / confusion: 73.60% / [[215, 140], [105, 468]], * Val accuracy / confusion: 73.90% / [[128, 102], [52, 308]] ------------------------------ Epoch 034 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.647362 - Iter 028 / 029, Loss: 0.479482 * Train accuracy / confusion: 73.81% / [[210, 148], [95, 475]], * Val accuracy / confusion: 68.31% / [[184, 46], [141, 219]] ------------------------------ Epoch 035 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.550135 - Iter 028 / 029, Loss: 0.455041 * Train accuracy / confusion: 74.25% / [[216, 145], [94, 473]], * Val accuracy / confusion: 72.54% / [[87, 143], [19, 341]] ------------------------------ Epoch 036 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.603955 - Iter 028 / 029, Loss: 0.591803 * Train accuracy / confusion: 74.03% / [[233, 131], [110, 454]], * Val accuracy / confusion: 76.44% / [[121, 109], [30, 330]] ------------------------------ Epoch 037 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.511180 - Iter 028 / 029, Loss: 0.499753 * Train accuracy / confusion: 74.14% / [[218, 145], [95, 470]], * Val accuracy / confusion: 70.00% / [[188, 42], [135, 225]] ------------------------------ Epoch 038 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.489841 - Iter 028 / 029, Loss: 0.480828 * Train accuracy / confusion: 74.46% / [[220, 141], [96, 471]], * Val accuracy / confusion: 66.95% / [[38, 192], [3, 357]] ------------------------------ Epoch 039 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.420153 - Iter 028 / 029, Loss: 0.421544 * Train accuracy / confusion: 74.14% / [[227, 139], [101, 461]], * Val accuracy / confusion: 72.20% / [[170, 60], [104, 256]] ------------------------------ Epoch 040 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.451115 - Iter 028 / 029, Loss: 0.537000 * Train accuracy / confusion: 74.25% / [[226, 136], [103, 463]], * Val accuracy / confusion: 75.08% / [[119, 111], [36, 324]] ------------------------------ Epoch 041 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.532969 - Iter 028 / 029, Loss: 0.473312 * Train accuracy / confusion: 74.57% / [[215, 148], [88, 477]], * Val accuracy / confusion: 73.05% / [[101, 129], [30, 330]] ------------------------------ Epoch 042 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.485807 - Iter 028 / 029, Loss: 0.631229 * Train accuracy / confusion: 72.95% / [[217, 143], [108, 460]], * Val accuracy / confusion: 73.22% / [[87, 143], [15, 345]] ------------------------------ Epoch 043 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.609160 - Iter 028 / 029, Loss: 0.609701 * Train accuracy / confusion: 74.14% / [[219, 142], [98, 469]], * Val accuracy / confusion: 76.10% / [[161, 69], [72, 288]] ------------------------------ Epoch 044 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.458777 - Iter 028 / 029, Loss: 0.604419 * Train accuracy / confusion: 73.81% / [[220, 140], [103, 465]], * Val accuracy / confusion: 75.25% / [[153, 77], [69, 291]] ------------------------------ Epoch 045 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.430115 - Iter 028 / 029, Loss: 0.498915 * Train accuracy / confusion: 74.03% / [[211, 151], [90, 476]], * Val accuracy / confusion: 71.19% / [[85, 145], [25, 335]] ------------------------------ Epoch 046 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.464470 - Iter 028 / 029, Loss: 0.461482 * Train accuracy / confusion: 75.11% / [[222, 141], [90, 475]], * Val accuracy / confusion: 72.03% / [[157, 73], [92, 268]] ------------------------------ Epoch 047 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.586823 - Iter 028 / 029, Loss: 0.516701 * Train accuracy / confusion: 74.68% / [[217, 145], [90, 476]], * Val accuracy / confusion: 72.54% / [[163, 67], [95, 265]] ------------------------------ Epoch 048 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.467314 - Iter 028 / 029, Loss: 0.400910 * Train accuracy / confusion: 74.57% / [[219, 143], [93, 473]], * Val accuracy / confusion: 74.75% / [[136, 94], [55, 305]] ------------------------------ Epoch 049 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.455569 - Iter 028 / 029, Loss: 0.593278 * Train accuracy / confusion: 75.97% / [[226, 135], [88, 479]], * Val accuracy / confusion: 62.20% / [[198, 32], [191, 169]] ------------------------------ Epoch 050 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.541898 - Iter 028 / 029, Loss: 0.519106 * Train accuracy / confusion: 76.94% / [[233, 130], [84, 481]], * Val accuracy / confusion: 74.75% / [[137, 93], [56, 304]] ------------------------------ Epoch 051 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.461812 - Iter 028 / 029, Loss: 0.561162 * Train accuracy / confusion: 73.60% / [[209, 153], [92, 474]], * Val accuracy / confusion: 74.75% / [[109, 121], [28, 332]] ------------------------------ Epoch 052 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.686395 - Iter 028 / 029, Loss: 0.675046 * Train accuracy / confusion: 74.35% / [[219, 141], [97, 471]], * Val accuracy / confusion: 73.90% / [[111, 119], [35, 325]] ------------------------------ Epoch 053 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.682407 - Iter 028 / 029, Loss: 0.408368 * Train accuracy / confusion: 75.97% / [[235, 129], [94, 470]], * Val accuracy / confusion: 71.53% / [[72, 158], [10, 350]] ------------------------------ Epoch 054 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.492123 - Iter 028 / 029, Loss: 0.542685 * Train accuracy / confusion: 76.08% / [[226, 137], [85, 480]], * Val accuracy / confusion: 68.81% / [[177, 53], [131, 229]] ------------------------------ Epoch 055 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.568456 - Iter 028 / 029, Loss: 0.465527 * Train accuracy / confusion: 74.35% / [[207, 155], [83, 483]], * Val accuracy / confusion: 71.53% / [[168, 62], [106, 254]] ------------------------------ Epoch 056 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.522690 - Iter 028 / 029, Loss: 0.483667 * Train accuracy / confusion: 75.00% / [[223, 135], [97, 473]], * Val accuracy / confusion: 72.88% / [[161, 69], [91, 269]] ------------------------------ Epoch 057 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.475738 - Iter 028 / 029, Loss: 0.621266 * Train accuracy / confusion: 74.14% / [[208, 157], [83, 480]], * Val accuracy / confusion: 73.73% / [[151, 79], [76, 284]] ------------------------------ Epoch 058 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.761177 - Iter 028 / 029, Loss: 0.646525 * Train accuracy / confusion: 75.00% / [[234, 129], [103, 462]], * Val accuracy / confusion: 74.07% / [[132, 98], [55, 305]] ------------------------------ Epoch 059 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.385408 - Iter 028 / 029, Loss: 0.616260 * Train accuracy / confusion: 75.65% / [[229, 129], [97, 473]], * Val accuracy / confusion: 72.03% / [[95, 135], [30, 330]] ------------------------------ Epoch 060 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.497723 - Iter 028 / 029, Loss: 0.332670 * Train accuracy / confusion: 76.29% / [[223, 135], [85, 485]], * Val accuracy / confusion: 74.24% / [[116, 114], [38, 322]] ------------------------------ Epoch 061 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.463461 - Iter 028 / 029, Loss: 0.544525 * Train accuracy / confusion: 76.19% / [[223, 140], [81, 484]], * Val accuracy / confusion: 76.10% / [[151, 79], [62, 298]] ------------------------------ Epoch 062 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.410450 - Iter 028 / 029, Loss: 0.458128 * Train accuracy / confusion: 74.14% / [[212, 151], [89, 476]], * Val accuracy / confusion: 75.08% / [[109, 121], [26, 334]] ------------------------------ Epoch 063 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.557521 - Iter 028 / 029, Loss: 0.596670 * Train accuracy / confusion: 74.35% / [[217, 145], [93, 473]], * Val accuracy / confusion: 77.12% / [[136, 94], [41, 319]] ------------------------------ Epoch 064 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.444364 - Iter 028 / 029, Loss: 0.359691 * Train accuracy / confusion: 75.54% / [[218, 142], [85, 483]], * Val accuracy / confusion: 74.07% / [[165, 65], [88, 272]] ------------------------------ Epoch 065 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.604953 - Iter 028 / 029, Loss: 0.472783 * Train accuracy / confusion: 76.62% / [[225, 137], [80, 486]], * Val accuracy / confusion: 74.58% / [[118, 112], [38, 322]] ------------------------------ Epoch 066 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.462388 - Iter 028 / 029, Loss: 0.558146 * Train accuracy / confusion: 76.08% / [[232, 132], [90, 474]], * Val accuracy / confusion: 76.27% / [[133, 97], [43, 317]] ------------------------------ Epoch 067 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.466160 - Iter 028 / 029, Loss: 0.568735 * Train accuracy / confusion: 75.86% / [[221, 138], [86, 483]], * Val accuracy / confusion: 73.73% / [[125, 105], [50, 310]] ------------------------------ Epoch 068 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.553492 - Iter 028 / 029, Loss: 0.526521 * Train accuracy / confusion: 75.75% / [[224, 140], [85, 479]], * Val accuracy / confusion: 72.54% / [[131, 99], [63, 297]] ------------------------------ Epoch 069 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.380616 - Iter 028 / 029, Loss: 0.568141 * Train accuracy / confusion: 75.54% / [[227, 135], [92, 474]], * Val accuracy / confusion: 75.59% / [[156, 74], [70, 290]] ------------------------------ Epoch 070 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.484084 - Iter 028 / 029, Loss: 0.447260 * Train accuracy / confusion: 77.16% / [[230, 132], [80, 486]], * Val accuracy / confusion: 74.92% / [[155, 75], [73, 287]] ------------------------------ Epoch 071 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.439582 - Iter 028 / 029, Loss: 0.495455 * Train accuracy / confusion: 75.65% / [[225, 138], [88, 477]], * Val accuracy / confusion: 73.39% / [[147, 83], [74, 286]] ------------------------------ Epoch 072 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.454334 - Iter 028 / 029, Loss: 0.526294 * Train accuracy / confusion: 76.62% / [[222, 142], [75, 489]], * Val accuracy / confusion: 75.08% / [[101, 129], [18, 342]] ------------------------------ Epoch 073 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.451261 - Iter 028 / 029, Loss: 0.407618 * Train accuracy / confusion: 76.83% / [[233, 127], [88, 480]], * Val accuracy / confusion: 75.76% / [[125, 105], [38, 322]] ------------------------------ Epoch 074 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.375085 - Iter 028 / 029, Loss: 0.422529 * Train accuracy / confusion: 75.86% / [[218, 146], [78, 486]], * Val accuracy / confusion: 69.15% / [[179, 51], [131, 229]] ------------------------------ Epoch 075 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.586300 - Iter 028 / 029, Loss: 0.488016 * Train accuracy / confusion: 76.62% / [[243, 121], [96, 468]], * Val accuracy / confusion: 75.76% / [[112, 118], [25, 335]] ------------------------------ Epoch 076 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.531547 - Iter 028 / 029, Loss: 0.608338 * Train accuracy / confusion: 76.94% / [[232, 133], [81, 482]], * Val accuracy / confusion: 73.56% / [[155, 75], [81, 279]] ------------------------------ Epoch 077 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.441162 - Iter 028 / 029, Loss: 0.459905 * Train accuracy / confusion: 76.19% / [[233, 129], [92, 474]], * Val accuracy / confusion: 72.71% / [[102, 128], [33, 327]] ------------------------------ Epoch 078 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.635758 - Iter 028 / 029, Loss: 0.464953 * Train accuracy / confusion: 76.72% / [[232, 133], [83, 480]], * Val accuracy / confusion: 73.05% / [[161, 69], [90, 270]] ------------------------------ Epoch 079 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.595157 - Iter 028 / 029, Loss: 0.532015 * Train accuracy / confusion: 75.86% / [[233, 132], [92, 471]], * Val accuracy / confusion: 75.25% / [[129, 101], [45, 315]] ------------------------------ Epoch 080 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.423463 - Iter 028 / 029, Loss: 0.425904 * Train accuracy / confusion: 76.08% / [[218, 144], [78, 488]], * Val accuracy / confusion: 75.08% / [[134, 96], [51, 309]] ------------------------------ Epoch 081 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.361284 - Iter 028 / 029, Loss: 0.515291 * Train accuracy / confusion: 76.72% / [[237, 123], [93, 475]], * Val accuracy / confusion: 74.41% / [[145, 85], [66, 294]] ------------------------------ Epoch 082 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.541505 - Iter 028 / 029, Loss: 0.488222 * Train accuracy / confusion: 75.65% / [[232, 132], [94, 470]], * Val accuracy / confusion: 70.85% / [[175, 55], [117, 243]] ------------------------------ Epoch 083 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.583653 - Iter 028 / 029, Loss: 0.467007 * Train accuracy / confusion: 75.75% / [[242, 119], [106, 461]], * Val accuracy / confusion: 75.08% / [[112, 118], [29, 331]] ------------------------------ Epoch 084 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.487074 - Iter 028 / 029, Loss: 0.503133 * Train accuracy / confusion: 76.08% / [[232, 132], [90, 474]], * Val accuracy / confusion: 72.37% / [[83, 147], [16, 344]] ------------------------------ Epoch 085 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.429332 - Iter 028 / 029, Loss: 0.477314 * Train accuracy / confusion: 76.29% / [[222, 138], [82, 486]], * Val accuracy / confusion: 76.10% / [[137, 93], [48, 312]] ------------------------------ Epoch 086 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.470304 - Iter 028 / 029, Loss: 0.476995 * Train accuracy / confusion: 75.75% / [[228, 136], [89, 475]], * Val accuracy / confusion: 74.75% / [[137, 93], [56, 304]] ------------------------------ Epoch 087 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.579012 - Iter 028 / 029, Loss: 0.578450 * Train accuracy / confusion: 77.16% / [[235, 128], [84, 481]], * Val accuracy / confusion: 76.95% / [[151, 79], [57, 303]] ------------------------------ Epoch 088 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.558710 - Iter 028 / 029, Loss: 0.391678 * Train accuracy / confusion: 76.51% / [[235, 127], [91, 475]], * Val accuracy / confusion: 72.37% / [[167, 63], [100, 260]] ------------------------------ Epoch 089 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.622175 - Iter 028 / 029, Loss: 0.600782 * Train accuracy / confusion: 77.16% / [[236, 125], [87, 480]], * Val accuracy / confusion: 74.58% / [[119, 111], [39, 321]] ------------------------------ Epoch 090 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.672663 - Iter 028 / 029, Loss: 0.442640 * Train accuracy / confusion: 77.59% / [[232, 127], [81, 488]], * Val accuracy / confusion: 73.39% / [[121, 109], [48, 312]] ------------------------------ Epoch 091 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.482572 - Iter 028 / 029, Loss: 0.512450 * Train accuracy / confusion: 75.86% / [[241, 120], [104, 463]], * Val accuracy / confusion: 74.24% / [[108, 122], [30, 330]] ------------------------------ Epoch 092 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.488269 - Iter 028 / 029, Loss: 0.463167 * Train accuracy / confusion: 76.29% / [[225, 136], [84, 483]], * Val accuracy / confusion: 73.90% / [[135, 95], [59, 301]] ------------------------------ Epoch 093 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.577154 - Iter 028 / 029, Loss: 0.671266 * Train accuracy / confusion: 74.57% / [[219, 143], [93, 473]], * Val accuracy / confusion: 75.42% / [[126, 104], [41, 319]] ------------------------------ Epoch 094 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.427585 - Iter 028 / 029, Loss: 0.553115 * Train accuracy / confusion: 77.59% / [[230, 132], [76, 490]], * Val accuracy / confusion: 75.93% / [[130, 100], [42, 318]] ------------------------------ Epoch 095 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.332805 - Iter 028 / 029, Loss: 0.521802 * Train accuracy / confusion: 77.69% / [[242, 120], [87, 479]], * Val accuracy / confusion: 68.98% / [[183, 47], [136, 224]] ------------------------------ Epoch 096 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.457146 - Iter 028 / 029, Loss: 0.611440 * Train accuracy / confusion: 75.97% / [[222, 140], [83, 483]], * Val accuracy / confusion: 71.69% / [[83, 147], [20, 340]] ------------------------------ Epoch 097 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.565841 - Iter 028 / 029, Loss: 0.471492 * Train accuracy / confusion: 78.34% / [[246, 119], [82, 481]], * Val accuracy / confusion: 73.22% / [[169, 61], [97, 263]] ------------------------------ Epoch 098 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.502653 - Iter 028 / 029, Loss: 0.505740 * Train accuracy / confusion: 77.69% / [[226, 133], [74, 495]], * Val accuracy / confusion: 74.07% / [[137, 93], [60, 300]] ------------------------------ Epoch 099 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.680466 - Iter 028 / 029, Loss: 0.410744 * Train accuracy / confusion: 76.72% / [[246, 118], [98, 466]], * Val accuracy / confusion: 71.19% / [[170, 60], [110, 250]] ------------------------------ Epoch 100 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.494486 - Iter 028 / 029, Loss: 0.763107 * Train accuracy / confusion: 76.72% / [[226, 137], [79, 486]], * Val accuracy / confusion: 70.51% / [[109, 121], [53, 307]] ------------------------------ Epoch 101 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.582751 - Iter 028 / 029, Loss: 0.505413 * Train accuracy / confusion: 77.80% / [[249, 113], [93, 473]], * Val accuracy / confusion: 77.46% / [[128, 102], [31, 329]] ------------------------------ Epoch 102 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.405778 - Iter 028 / 029, Loss: 0.464042 * Train accuracy / confusion: 75.97% / [[241, 122], [101, 464]], * Val accuracy / confusion: 71.86% / [[147, 83], [83, 277]] ------------------------------ Epoch 103 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.401300 - Iter 028 / 029, Loss: 0.359713 * Train accuracy / confusion: 77.37% / [[226, 138], [72, 492]], * Val accuracy / confusion: 74.92% / [[114, 116], [32, 328]] ------------------------------ Epoch 104 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.433190 - Iter 028 / 029, Loss: 0.495798 * Train accuracy / confusion: 77.69% / [[246, 117], [90, 475]], * Val accuracy / confusion: 74.92% / [[125, 105], [43, 317]] ------------------------------ Epoch 105 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.639521 - Iter 028 / 029, Loss: 0.359415 * Train accuracy / confusion: 76.40% / [[235, 128], [91, 474]], * Val accuracy / confusion: 73.39% / [[158, 72], [85, 275]] ------------------------------ Epoch 106 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.618396 - Iter 028 / 029, Loss: 0.531591 * Train accuracy / confusion: 75.54% / [[225, 138], [89, 476]], * Val accuracy / confusion: 75.59% / [[126, 104], [40, 320]] ------------------------------ Epoch 107 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.591650 - Iter 028 / 029, Loss: 0.418108 * Train accuracy / confusion: 76.72% / [[236, 128], [88, 476]], * Val accuracy / confusion: 74.07% / [[174, 56], [97, 263]] ------------------------------ Epoch 108 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.451980 - Iter 028 / 029, Loss: 0.411743 * Train accuracy / confusion: 76.72% / [[237, 127], [89, 475]], * Val accuracy / confusion: 75.25% / [[128, 102], [44, 316]] ------------------------------ Epoch 109 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.556077 - Iter 028 / 029, Loss: 0.632576 * Train accuracy / confusion: 76.94% / [[212, 146], [68, 502]], * Val accuracy / confusion: 74.07% / [[142, 88], [65, 295]] ------------------------------ Epoch 110 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.441070 - Iter 028 / 029, Loss: 0.434506 * Train accuracy / confusion: 77.59% / [[245, 112], [96, 475]], * Val accuracy / confusion: 77.29% / [[132, 98], [36, 324]] ------------------------------ Epoch 111 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.470521 - Iter 028 / 029, Loss: 0.434859 * Train accuracy / confusion: 77.91% / [[236, 126], [79, 487]], * Val accuracy / confusion: 74.75% / [[112, 118], [31, 329]] ------------------------------ Epoch 112 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.526072 - Iter 028 / 029, Loss: 0.568176 * Train accuracy / confusion: 75.11% / [[223, 137], [94, 474]], * Val accuracy / confusion: 66.27% / [[185, 45], [154, 206]] ------------------------------ Epoch 113 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.501058 - Iter 028 / 029, Loss: 0.329307 * Train accuracy / confusion: 76.29% / [[224, 137], [83, 484]], * Val accuracy / confusion: 74.41% / [[135, 95], [56, 304]] ------------------------------ Epoch 114 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.478989 - Iter 028 / 029, Loss: 0.588478 * Train accuracy / confusion: 76.19% / [[239, 123], [98, 468]], * Val accuracy / confusion: 76.61% / [[125, 105], [33, 327]] ------------------------------ Epoch 115 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.347963 - Iter 028 / 029, Loss: 0.786324 * Train accuracy / confusion: 75.97% / [[217, 145], [78, 488]], * Val accuracy / confusion: 71.69% / [[134, 96], [71, 289]] ------------------------------ Epoch 116 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.396239 - Iter 028 / 029, Loss: 0.595580 * Train accuracy / confusion: 77.91% / [[244, 119], [86, 479]], * Val accuracy / confusion: 75.25% / [[159, 71], [75, 285]] ------------------------------ Epoch 117 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.385247 - Iter 028 / 029, Loss: 0.414658 * Train accuracy / confusion: 77.26% / [[241, 121], [90, 476]], * Val accuracy / confusion: 73.56% / [[143, 87], [69, 291]] ------------------------------ Epoch 118 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.665694 - Iter 028 / 029, Loss: 0.365169 * Train accuracy / confusion: 77.05% / [[234, 127], [86, 481]], * Val accuracy / confusion: 74.41% / [[149, 81], [70, 290]] ------------------------------ Epoch 119 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.583692 - Iter 028 / 029, Loss: 0.437262 * Train accuracy / confusion: 76.51% / [[223, 134], [84, 487]], * Val accuracy / confusion: 71.53% / [[133, 97], [71, 289]] ------------------------------ Epoch 120 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.392352 - Iter 028 / 029, Loss: 0.517217 * Train accuracy / confusion: 77.91% / [[247, 114], [91, 476]], * Val accuracy / confusion: 71.53% / [[153, 77], [91, 269]] ------------------------------ Epoch 121 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.518908 - Iter 028 / 029, Loss: 0.491713 * Train accuracy / confusion: 77.69% / [[247, 114], [93, 474]], * Val accuracy / confusion: 73.56% / [[145, 85], [71, 289]] ------------------------------ Epoch 122 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.480852 - Iter 028 / 029, Loss: 0.508742 * Train accuracy / confusion: 79.20% / [[238, 122], [71, 497]], * Val accuracy / confusion: 72.88% / [[124, 106], [54, 306]] ------------------------------ Epoch 123 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.353265 - Iter 028 / 029, Loss: 0.641570 * Train accuracy / confusion: 76.94% / [[223, 136], [78, 491]], * Val accuracy / confusion: 72.54% / [[157, 73], [89, 271]] ------------------------------ Epoch 124 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.412329 - Iter 028 / 029, Loss: 0.350854 * Train accuracy / confusion: 77.05% / [[239, 120], [93, 476]], * Val accuracy / confusion: 73.73% / [[129, 101], [54, 306]] ------------------------------ Epoch 125 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.429985 - Iter 028 / 029, Loss: 0.467732 * Train accuracy / confusion: 76.72% / [[234, 129], [87, 478]], * Val accuracy / confusion: 72.20% / [[140, 90], [74, 286]] ------------------------------ Epoch 126 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.568819 - Iter 028 / 029, Loss: 0.641667 * Train accuracy / confusion: 77.37% / [[224, 137], [73, 494]], * Val accuracy / confusion: 73.73% / [[127, 103], [52, 308]] ------------------------------ Epoch 127 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.542055 - Iter 028 / 029, Loss: 0.385817 * Train accuracy / confusion: 78.77% / [[243, 118], [79, 488]], * Val accuracy / confusion: 73.90% / [[149, 81], [73, 287]] ------------------------------ Epoch 128 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.393545 - Iter 028 / 029, Loss: 0.355786 * Train accuracy / confusion: 76.94% / [[224, 133], [81, 490]], * Val accuracy / confusion: 72.37% / [[105, 125], [38, 322]] ------------------------------ Epoch 129 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.451413 - Iter 028 / 029, Loss: 0.500196 * Train accuracy / confusion: 77.26% / [[227, 132], [79, 490]], * Val accuracy / confusion: 74.07% / [[155, 75], [78, 282]] ------------------------------ Epoch 130 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.553584 - Iter 028 / 029, Loss: 0.501815 * Train accuracy / confusion: 76.40% / [[215, 146], [73, 494]], * Val accuracy / confusion: 74.24% / [[111, 119], [33, 327]] ------------------------------ Epoch 131 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.456186 - Iter 028 / 029, Loss: 0.311944 * Train accuracy / confusion: 78.99% / [[250, 109], [86, 483]], * Val accuracy / confusion: 70.85% / [[142, 88], [84, 276]] ------------------------------ Epoch 132 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.426160 - Iter 028 / 029, Loss: 0.534353 * Train accuracy / confusion: 76.40% / [[232, 130], [89, 477]], * Val accuracy / confusion: 74.24% / [[120, 110], [42, 318]] ------------------------------ Epoch 133 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.502366 - Iter 028 / 029, Loss: 0.471591 * Train accuracy / confusion: 77.37% / [[223, 142], [68, 495]], * Val accuracy / confusion: 72.20% / [[140, 90], [74, 286]] ------------------------------ Epoch 134 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.589523 - Iter 028 / 029, Loss: 0.494793 * Train accuracy / confusion: 77.91% / [[231, 128], [77, 492]], * Val accuracy / confusion: 73.90% / [[146, 84], [70, 290]] ------------------------------ Epoch 135 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.776718 - Iter 028 / 029, Loss: 0.523945 * Train accuracy / confusion: 76.19% / [[234, 131], [90, 473]], * Val accuracy / confusion: 74.75% / [[144, 86], [63, 297]] ------------------------------ Epoch 136 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.353653 - Iter 028 / 029, Loss: 0.466899 * Train accuracy / confusion: 79.31% / [[242, 120], [72, 494]], * Val accuracy / confusion: 75.08% / [[131, 99], [48, 312]] ------------------------------ Epoch 137 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.458354 - Iter 028 / 029, Loss: 0.456072 * Train accuracy / confusion: 77.48% / [[238, 124], [85, 481]], * Val accuracy / confusion: 73.73% / [[140, 90], [65, 295]] ------------------------------ Epoch 138 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.466041 - Iter 028 / 029, Loss: 0.433754 * Train accuracy / confusion: 78.77% / [[248, 112], [85, 483]], * Val accuracy / confusion: 70.34% / [[153, 77], [98, 262]] ------------------------------ Epoch 139 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.692836 - Iter 028 / 029, Loss: 0.536608 * Train accuracy / confusion: 75.97% / [[210, 149], [74, 495]], * Val accuracy / confusion: 74.41% / [[130, 100], [51, 309]] ------------------------------ Epoch 140 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.547553 - Iter 028 / 029, Loss: 0.500338 * Train accuracy / confusion: 77.69% / [[247, 118], [89, 474]], * Val accuracy / confusion: 72.03% / [[145, 85], [80, 280]] ------------------------------ Epoch 141 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.450882 - Iter 028 / 029, Loss: 0.731702 * Train accuracy / confusion: 77.69% / [[239, 119], [88, 482]], * Val accuracy / confusion: 74.07% / [[129, 101], [52, 308]] ------------------------------ Epoch 142 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.428456 - Iter 028 / 029, Loss: 0.553867 * Train accuracy / confusion: 78.34% / [[241, 122], [79, 486]], * Val accuracy / confusion: 74.75% / [[138, 92], [57, 303]] ------------------------------ Epoch 143 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.459609 - Iter 028 / 029, Loss: 0.531137 * Train accuracy / confusion: 76.83% / [[225, 132], [83, 488]], * Val accuracy / confusion: 69.66% / [[96, 134], [45, 315]] ------------------------------ Epoch 144 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.393156 - Iter 028 / 029, Loss: 0.350490 * Train accuracy / confusion: 77.48% / [[230, 131], [78, 489]], * Val accuracy / confusion: 73.73% / [[150, 80], [75, 285]] ------------------------------ Epoch 145 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.429979 - Iter 028 / 029, Loss: 0.471414 * Train accuracy / confusion: 77.80% / [[231, 129], [77, 491]], * Val accuracy / confusion: 74.58% / [[136, 94], [56, 304]] ------------------------------ Epoch 146 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.535407 - Iter 028 / 029, Loss: 0.498909 * Train accuracy / confusion: 77.91% / [[239, 122], [83, 484]], * Val accuracy / confusion: 73.73% / [[129, 101], [54, 306]] ------------------------------ Epoch 147 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.713842 - Iter 028 / 029, Loss: 0.467538 * Train accuracy / confusion: 77.26% / [[237, 123], [88, 480]], * Val accuracy / confusion: 73.73% / [[163, 67], [88, 272]] ------------------------------ Epoch 148 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.459075 - Iter 028 / 029, Loss: 0.479708 * Train accuracy / confusion: 77.91% / [[237, 126], [79, 486]], * Val accuracy / confusion: 75.59% / [[132, 98], [46, 314]] ------------------------------ Epoch 149 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.536430 - Iter 028 / 029, Loss: 0.418803 * Train accuracy / confusion: 77.26% / [[232, 127], [84, 485]], * Val accuracy / confusion: 74.41% / [[120, 110], [41, 319]] ------------------------------ Epoch 150 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.646911 - Iter 028 / 029, Loss: 0.501914 * Train accuracy / confusion: 76.83% / [[227, 137], [78, 486]], * Val accuracy / confusion: 72.88% / [[132, 98], [62, 298]] ------------------------------ Epoch 151 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.468422 - Iter 028 / 029, Loss: 0.431433 * Train accuracy / confusion: 75.97% / [[225, 137], [86, 480]], * Val accuracy / confusion: 75.93% / [[149, 81], [61, 299]] ------------------------------ Epoch 152 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.343869 - Iter 028 / 029, Loss: 0.450140 * Train accuracy / confusion: 75.86% / [[224, 141], [83, 480]], * Val accuracy / confusion: 74.24% / [[130, 100], [52, 308]] ------------------------------ Epoch 153 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.570454 - Iter 028 / 029, Loss: 0.475184 * Train accuracy / confusion: 77.59% / [[237, 126], [82, 483]], * Val accuracy / confusion: 74.07% / [[151, 79], [74, 286]] ------------------------------ Epoch 154 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.436480 - Iter 028 / 029, Loss: 0.387715 * Train accuracy / confusion: 76.94% / [[232, 132], [82, 482]], * Val accuracy / confusion: 73.22% / [[93, 137], [21, 339]] ------------------------------ Epoch 155 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.495438 - Iter 028 / 029, Loss: 0.400099 * Train accuracy / confusion: 78.23% / [[244, 119], [83, 482]], * Val accuracy / confusion: 73.05% / [[148, 82], [77, 283]] ------------------------------ Epoch 156 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.453451 - Iter 028 / 029, Loss: 0.320825 * Train accuracy / confusion: 77.91% / [[232, 129], [76, 491]], * Val accuracy / confusion: 72.20% / [[130, 100], [64, 296]] ------------------------------ Epoch 157 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.331059 - Iter 028 / 029, Loss: 0.404265 * Train accuracy / confusion: 78.45% / [[250, 109], [91, 478]], * Val accuracy / confusion: 72.37% / [[142, 88], [75, 285]] ------------------------------ Epoch 158 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.529685 - Iter 028 / 029, Loss: 0.431136 * Train accuracy / confusion: 77.80% / [[229, 133], [73, 493]], * Val accuracy / confusion: 74.92% / [[139, 91], [57, 303]] ------------------------------ Epoch 159 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.451557 - Iter 028 / 029, Loss: 0.453181 * Train accuracy / confusion: 77.05% / [[236, 125], [88, 479]], * Val accuracy / confusion: 68.98% / [[154, 76], [107, 253]] ------------------------------ Epoch 160 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.469417 - Iter 028 / 029, Loss: 0.524808 * Train accuracy / confusion: 77.05% / [[229, 132], [81, 486]], * Val accuracy / confusion: 72.37% / [[142, 88], [75, 285]] ------------------------------ Epoch 161 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.585358 - Iter 028 / 029, Loss: 0.363034 * Train accuracy / confusion: 78.12% / [[235, 127], [76, 490]], * Val accuracy / confusion: 74.41% / [[131, 99], [52, 308]] ------------------------------ Epoch 162 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.617065 - Iter 028 / 029, Loss: 0.520208 * Train accuracy / confusion: 75.43% / [[234, 130], [98, 466]], * Val accuracy / confusion: 74.58% / [[141, 89], [61, 299]] ------------------------------ Epoch 163 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.585363 - Iter 028 / 029, Loss: 0.682366 * Train accuracy / confusion: 77.05% / [[232, 123], [90, 483]], * Val accuracy / confusion: 72.03% / [[141, 89], [76, 284]] ------------------------------ Epoch 164 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.572904 - Iter 028 / 029, Loss: 0.337293 * Train accuracy / confusion: 78.99% / [[238, 123], [72, 495]], * Val accuracy / confusion: 74.75% / [[152, 78], [71, 289]] ------------------------------ Epoch 165 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.388123 - Iter 028 / 029, Loss: 0.484769 * Train accuracy / confusion: 77.91% / [[244, 120], [85, 479]], * Val accuracy / confusion: 72.20% / [[162, 68], [96, 264]] ------------------------------ Epoch 166 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.508077 - Iter 028 / 029, Loss: 0.836212 * Train accuracy / confusion: 77.80% / [[232, 131], [75, 490]], * Val accuracy / confusion: 73.90% / [[109, 121], [33, 327]] ------------------------------ Epoch 167 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.374466 - Iter 028 / 029, Loss: 0.467359 * Train accuracy / confusion: 76.51% / [[223, 143], [75, 487]], * Val accuracy / confusion: 76.61% / [[133, 97], [41, 319]] ------------------------------ Epoch 168 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.537741 - Iter 028 / 029, Loss: 0.677388 * Train accuracy / confusion: 77.37% / [[242, 123], [87, 476]], * Val accuracy / confusion: 75.93% / [[150, 80], [62, 298]] ------------------------------ Epoch 169 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.487610 - Iter 028 / 029, Loss: 0.522652 * Train accuracy / confusion: 77.37% / [[240, 124], [86, 478]], * Val accuracy / confusion: 74.24% / [[169, 61], [91, 269]] ------------------------------ Epoch 170 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.709485 - Iter 028 / 029, Loss: 0.560517 * Train accuracy / confusion: 76.94% / [[228, 134], [80, 486]], * Val accuracy / confusion: 73.22% / [[132, 98], [60, 300]] ------------------------------ Epoch 171 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.489354 - Iter 028 / 029, Loss: 0.395028 * Train accuracy / confusion: 78.02% / [[233, 127], [77, 491]], * Val accuracy / confusion: 71.86% / [[159, 71], [95, 265]] ------------------------------ Epoch 172 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.372398 - Iter 028 / 029, Loss: 0.685245 * Train accuracy / confusion: 77.91% / [[245, 119], [86, 478]], * Val accuracy / confusion: 74.75% / [[141, 89], [60, 300]] ------------------------------ Epoch 173 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.402504 - Iter 028 / 029, Loss: 0.678126 * Train accuracy / confusion: 77.37% / [[238, 125], [85, 480]], * Val accuracy / confusion: 73.90% / [[138, 92], [62, 298]] ------------------------------ Epoch 174 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.602438 - Iter 028 / 029, Loss: 0.372157 * Train accuracy / confusion: 78.88% / [[241, 119], [77, 491]], * Val accuracy / confusion: 71.86% / [[166, 64], [102, 258]] ------------------------------ Epoch 175 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.369122 - Iter 028 / 029, Loss: 0.430445 * Train accuracy / confusion: 77.69% / [[240, 124], [83, 481]], * Val accuracy / confusion: 74.07% / [[115, 115], [38, 322]] ------------------------------ Epoch 176 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.335590 - Iter 028 / 029, Loss: 0.455288 * Train accuracy / confusion: 76.94% / [[241, 120], [94, 473]], * Val accuracy / confusion: 74.92% / [[147, 83], [65, 295]] ------------------------------ Epoch 177 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.545812 - Iter 028 / 029, Loss: 0.377319 * Train accuracy / confusion: 77.80% / [[231, 127], [79, 491]], * Val accuracy / confusion: 75.76% / [[126, 104], [39, 321]] ------------------------------ Epoch 178 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.297183 - Iter 028 / 029, Loss: 0.465672 * Train accuracy / confusion: 78.56% / [[243, 119], [80, 486]], * Val accuracy / confusion: 75.08% / [[139, 91], [56, 304]] ------------------------------ Epoch 179 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.331991 - Iter 028 / 029, Loss: 0.491276 * Train accuracy / confusion: 78.12% / [[243, 120], [83, 482]], * Val accuracy / confusion: 74.07% / [[155, 75], [78, 282]] ------------------------------ Epoch 180 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.266149 - Iter 028 / 029, Loss: 0.452006 * Train accuracy / confusion: 78.66% / [[240, 122], [76, 490]], * Val accuracy / confusion: 73.90% / [[162, 68], [86, 274]] ------------------------------ Epoch 181 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.597618 - Iter 028 / 029, Loss: 0.361078 * Train accuracy / confusion: 79.63% / [[253, 107], [82, 486]], * Val accuracy / confusion: 72.54% / [[144, 86], [76, 284]] ------------------------------ Epoch 182 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.369757 - Iter 028 / 029, Loss: 0.292805 * Train accuracy / confusion: 78.45% / [[256, 108], [92, 472]], * Val accuracy / confusion: 72.71% / [[150, 80], [81, 279]] ------------------------------ Epoch 183 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.414444 - Iter 028 / 029, Loss: 0.348370 * Train accuracy / confusion: 79.31% / [[244, 117], [75, 492]], * Val accuracy / confusion: 72.54% / [[141, 89], [73, 287]] ------------------------------ Epoch 184 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.448002 - Iter 028 / 029, Loss: 0.482946 * Train accuracy / confusion: 78.88% / [[263, 102], [94, 469]], * Val accuracy / confusion: 71.86% / [[132, 98], [68, 292]] ------------------------------ Epoch 185 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.572643 - Iter 028 / 029, Loss: 0.679665 * Train accuracy / confusion: 77.48% / [[221, 139], [70, 498]], * Val accuracy / confusion: 72.03% / [[133, 97], [68, 292]] ------------------------------ Epoch 186 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.577922 - Iter 028 / 029, Loss: 0.565541 * Train accuracy / confusion: 78.02% / [[240, 120], [84, 484]], * Val accuracy / confusion: 74.24% / [[141, 89], [63, 297]] ------------------------------ Epoch 187 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.452846 - Iter 028 / 029, Loss: 0.421333 * Train accuracy / confusion: 77.91% / [[241, 124], [81, 482]], * Val accuracy / confusion: 71.36% / [[130, 100], [69, 291]] ------------------------------ Epoch 188 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.448886 - Iter 028 / 029, Loss: 0.352031 * Train accuracy / confusion: 77.48% / [[229, 131], [78, 490]], * Val accuracy / confusion: 71.53% / [[123, 107], [61, 299]] ------------------------------ Epoch 189 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.409348 - Iter 028 / 029, Loss: 0.543845 * Train accuracy / confusion: 76.51% / [[229, 133], [85, 481]], * Val accuracy / confusion: 73.56% / [[129, 101], [55, 305]] ------------------------------ Epoch 190 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.435826 - Iter 028 / 029, Loss: 0.494455 * Train accuracy / confusion: 78.02% / [[238, 125], [79, 486]], * Val accuracy / confusion: 71.53% / [[170, 60], [108, 252]] ------------------------------ Epoch 191 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.442677 - Iter 028 / 029, Loss: 0.375017 * Train accuracy / confusion: 78.77% / [[258, 107], [90, 473]], * Val accuracy / confusion: 74.07% / [[131, 99], [54, 306]] ------------------------------ Epoch 192 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.595005 - Iter 028 / 029, Loss: 0.616578 * Train accuracy / confusion: 77.91% / [[237, 126], [79, 486]], * Val accuracy / confusion: 74.07% / [[134, 96], [57, 303]] ------------------------------ Epoch 193 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.525545 - Iter 028 / 029, Loss: 0.417832 * Train accuracy / confusion: 77.59% / [[240, 121], [87, 480]], * Val accuracy / confusion: 74.75% / [[133, 97], [52, 308]] ------------------------------ Epoch 194 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.377137 - Iter 028 / 029, Loss: 0.405476 * Train accuracy / confusion: 78.45% / [[239, 123], [77, 489]], * Val accuracy / confusion: 72.54% / [[135, 95], [67, 293]] ------------------------------ Epoch 195 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.342741 - Iter 028 / 029, Loss: 0.685691 * Train accuracy / confusion: 78.88% / [[247, 115], [81, 485]], * Val accuracy / confusion: 73.90% / [[124, 106], [48, 312]] ------------------------------ Epoch 196 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.598929 - Iter 028 / 029, Loss: 0.423541 * Train accuracy / confusion: 79.31% / [[254, 110], [82, 482]], * Val accuracy / confusion: 71.69% / [[131, 99], [68, 292]] ------------------------------ Epoch 197 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.564700 - Iter 028 / 029, Loss: 0.540049 * Train accuracy / confusion: 78.12% / [[240, 119], [84, 485]], * Val accuracy / confusion: 72.54% / [[133, 97], [65, 295]] ------------------------------ Epoch 198 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.435314 - Iter 028 / 029, Loss: 0.466770 * Train accuracy / confusion: 80.71% / [[247, 115], [64, 502]], * Val accuracy / confusion: 73.90% / [[155, 75], [79, 281]] ------------------------------ Epoch 199 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.638351 - Iter 028 / 029, Loss: 0.365382 * Train accuracy / confusion: 77.16% / [[233, 129], [83, 483]], * Val accuracy / confusion: 74.24% / [[133, 97], [55, 305]] ------------------------------ Epoch 200 / 500, Learning rate: 1.92e-03 ------------------------------ - Iter 014 / 029, Loss: 0.567748 - Iter 028 / 029, Loss: 0.703160 * Train accuracy / confusion: 78.34% / [[239, 124], [77, 488]], * Val accuracy / confusion: 72.20% / [[129, 101], [63, 297]] ------------------------------ Epoch 201 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.481995 - Iter 028 / 029, Loss: 0.407458 * Train accuracy / confusion: 79.09% / [[248, 113], [81, 486]], * Val accuracy / confusion: 75.25% / [[155, 75], [71, 289]] ------------------------------ Epoch 202 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.558477 - Iter 028 / 029, Loss: 0.357850 * Train accuracy / confusion: 79.31% / [[253, 110], [82, 483]], * Val accuracy / confusion: 70.00% / [[135, 95], [82, 278]] ------------------------------ Epoch 203 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.446405 - Iter 028 / 029, Loss: 0.439719 * Train accuracy / confusion: 79.42% / [[251, 114], [77, 486]], * Val accuracy / confusion: 71.53% / [[133, 97], [71, 289]] ------------------------------ Epoch 204 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.547564 - Iter 028 / 029, Loss: 0.456539 * Train accuracy / confusion: 80.06% / [[251, 116], [69, 492]], * Val accuracy / confusion: 72.03% / [[129, 101], [64, 296]] ------------------------------ Epoch 205 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.536004 - Iter 028 / 029, Loss: 0.444154 * Train accuracy / confusion: 80.06% / [[258, 104], [81, 485]], * Val accuracy / confusion: 74.07% / [[144, 86], [67, 293]] ------------------------------ Epoch 206 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.386795 - Iter 028 / 029, Loss: 0.553015 * Train accuracy / confusion: 78.66% / [[245, 115], [83, 485]], * Val accuracy / confusion: 75.25% / [[151, 79], [67, 293]] ------------------------------ Epoch 207 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.470391 - Iter 028 / 029, Loss: 0.489517 * Train accuracy / confusion: 77.59% / [[240, 122], [86, 480]], * Val accuracy / confusion: 73.05% / [[148, 82], [77, 283]] ------------------------------ Epoch 208 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.394934 - Iter 028 / 029, Loss: 0.706627 * Train accuracy / confusion: 78.88% / [[244, 120], [76, 488]], * Val accuracy / confusion: 73.05% / [[142, 88], [71, 289]] ------------------------------ Epoch 209 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.578795 - Iter 028 / 029, Loss: 0.629795 * Train accuracy / confusion: 78.99% / [[246, 115], [80, 487]], * Val accuracy / confusion: 73.56% / [[143, 87], [69, 291]] ------------------------------ Epoch 210 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.370295 - Iter 028 / 029, Loss: 0.435172 * Train accuracy / confusion: 78.23% / [[241, 120], [82, 485]], * Val accuracy / confusion: 74.07% / [[138, 92], [61, 299]] ------------------------------ Epoch 211 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.513562 - Iter 028 / 029, Loss: 0.582146 * Train accuracy / confusion: 78.77% / [[247, 116], [81, 484]], * Val accuracy / confusion: 74.75% / [[138, 92], [57, 303]] ------------------------------ Epoch 212 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.447022 - Iter 028 / 029, Loss: 0.459862 * Train accuracy / confusion: 79.31% / [[250, 112], [80, 486]], * Val accuracy / confusion: 74.75% / [[144, 86], [63, 297]] ------------------------------ Epoch 213 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.444173 - Iter 028 / 029, Loss: 0.361794 * Train accuracy / confusion: 79.42% / [[249, 109], [82, 488]], * Val accuracy / confusion: 73.73% / [[143, 87], [68, 292]] ------------------------------ Epoch 214 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.521739 - Iter 028 / 029, Loss: 0.416395 * Train accuracy / confusion: 80.60% / [[253, 111], [69, 495]], * Val accuracy / confusion: 71.69% / [[140, 90], [77, 283]] ------------------------------ Epoch 215 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.448439 - Iter 028 / 029, Loss: 0.546322 * Train accuracy / confusion: 79.09% / [[248, 114], [80, 486]], * Val accuracy / confusion: 73.73% / [[137, 93], [62, 298]] ------------------------------ Epoch 216 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.403061 - Iter 028 / 029, Loss: 0.439311 * Train accuracy / confusion: 80.17% / [[260, 105], [79, 484]], * Val accuracy / confusion: 73.05% / [[138, 92], [67, 293]] ------------------------------ Epoch 217 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.377643 - Iter 028 / 029, Loss: 0.618030 * Train accuracy / confusion: 78.34% / [[253, 113], [88, 474]], * Val accuracy / confusion: 73.73% / [[141, 89], [66, 294]] ------------------------------ Epoch 218 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.480961 - Iter 028 / 029, Loss: 0.376299 * Train accuracy / confusion: 79.85% / [[256, 108], [79, 485]], * Val accuracy / confusion: 71.69% / [[138, 92], [75, 285]] ------------------------------ Epoch 219 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.384315 - Iter 028 / 029, Loss: 0.277055 * Train accuracy / confusion: 79.53% / [[256, 108], [82, 482]], * Val accuracy / confusion: 72.37% / [[152, 78], [85, 275]] ------------------------------ Epoch 220 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.360168 - Iter 028 / 029, Loss: 0.496145 * Train accuracy / confusion: 78.99% / [[252, 112], [83, 481]], * Val accuracy / confusion: 72.88% / [[143, 87], [73, 287]] ------------------------------ Epoch 221 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.539879 - Iter 028 / 029, Loss: 0.503718 * Train accuracy / confusion: 78.99% / [[247, 114], [81, 486]], * Val accuracy / confusion: 73.73% / [[148, 82], [73, 287]] ------------------------------ Epoch 222 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.410571 - Iter 028 / 029, Loss: 0.486147 * Train accuracy / confusion: 78.66% / [[249, 112], [86, 481]], * Val accuracy / confusion: 72.54% / [[149, 81], [81, 279]] ------------------------------ Epoch 223 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.347635 - Iter 028 / 029, Loss: 0.520536 * Train accuracy / confusion: 79.85% / [[254, 108], [79, 487]], * Val accuracy / confusion: 72.03% / [[135, 95], [70, 290]] ------------------------------ Epoch 224 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.543851 - Iter 028 / 029, Loss: 0.420293 * Train accuracy / confusion: 79.42% / [[251, 111], [80, 486]], * Val accuracy / confusion: 73.56% / [[144, 86], [70, 290]] ------------------------------ Epoch 225 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.448507 - Iter 028 / 029, Loss: 0.346060 * Train accuracy / confusion: 80.93% / [[252, 111], [66, 499]], * Val accuracy / confusion: 74.24% / [[136, 94], [58, 302]] ------------------------------ Epoch 226 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.332011 - Iter 028 / 029, Loss: 0.353624 * Train accuracy / confusion: 79.96% / [[260, 100], [86, 482]], * Val accuracy / confusion: 72.54% / [[144, 86], [76, 284]] ------------------------------ Epoch 227 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.742108 - Iter 028 / 029, Loss: 0.359894 * Train accuracy / confusion: 78.77% / [[242, 117], [80, 489]], * Val accuracy / confusion: 74.41% / [[146, 84], [67, 293]] ------------------------------ Epoch 228 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.525990 - Iter 028 / 029, Loss: 0.532835 * Train accuracy / confusion: 78.12% / [[247, 113], [90, 478]], * Val accuracy / confusion: 76.27% / [[149, 81], [59, 301]] ------------------------------ Epoch 229 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.360543 - Iter 028 / 029, Loss: 0.395978 * Train accuracy / confusion: 80.39% / [[249, 115], [67, 497]], * Val accuracy / confusion: 73.05% / [[145, 85], [74, 286]] ------------------------------ Epoch 230 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.514258 - Iter 028 / 029, Loss: 0.395047 * Train accuracy / confusion: 79.85% / [[245, 115], [72, 496]], * Val accuracy / confusion: 72.20% / [[137, 93], [71, 289]] ------------------------------ Epoch 231 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.512472 - Iter 028 / 029, Loss: 0.368686 * Train accuracy / confusion: 78.34% / [[244, 118], [83, 483]], * Val accuracy / confusion: 73.05% / [[141, 89], [70, 290]] ------------------------------ Epoch 232 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.539943 - Iter 028 / 029, Loss: 0.280065 * Train accuracy / confusion: 81.57% / [[257, 99], [72, 500]], * Val accuracy / confusion: 71.36% / [[143, 87], [82, 278]] ------------------------------ Epoch 233 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.340337 - Iter 028 / 029, Loss: 0.394597 * Train accuracy / confusion: 78.56% / [[242, 117], [82, 487]], * Val accuracy / confusion: 74.07% / [[148, 82], [71, 289]] ------------------------------ Epoch 234 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.319521 - Iter 028 / 029, Loss: 0.438940 * Train accuracy / confusion: 80.60% / [[256, 106], [74, 492]], * Val accuracy / confusion: 73.56% / [[145, 85], [71, 289]] ------------------------------ Epoch 235 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.322948 - Iter 028 / 029, Loss: 0.475488 * Train accuracy / confusion: 78.88% / [[248, 113], [83, 484]], * Val accuracy / confusion: 73.22% / [[139, 91], [67, 293]] ------------------------------ Epoch 236 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.376511 - Iter 028 / 029, Loss: 0.444967 * Train accuracy / confusion: 81.03% / [[262, 101], [75, 490]], * Val accuracy / confusion: 73.56% / [[142, 88], [68, 292]] ------------------------------ Epoch 237 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.404006 - Iter 028 / 029, Loss: 0.418996 * Train accuracy / confusion: 79.63% / [[251, 112], [77, 488]], * Val accuracy / confusion: 73.22% / [[142, 88], [70, 290]] ------------------------------ Epoch 238 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.431799 - Iter 028 / 029, Loss: 0.469531 * Train accuracy / confusion: 79.96% / [[254, 110], [76, 488]], * Val accuracy / confusion: 72.03% / [[145, 85], [80, 280]] ------------------------------ Epoch 239 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.503850 - Iter 028 / 029, Loss: 0.476457 * Train accuracy / confusion: 82.22% / [[262, 99], [66, 501]], * Val accuracy / confusion: 72.03% / [[145, 85], [80, 280]] ------------------------------ Epoch 240 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.425273 - Iter 028 / 029, Loss: 0.443642 * Train accuracy / confusion: 81.47% / [[258, 102], [70, 498]], * Val accuracy / confusion: 72.20% / [[139, 91], [73, 287]] ------------------------------ Epoch 241 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.762679 - Iter 028 / 029, Loss: 0.291245 * Train accuracy / confusion: 79.53% / [[256, 106], [84, 482]], * Val accuracy / confusion: 72.20% / [[146, 84], [80, 280]] ------------------------------ Epoch 242 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.627124 - Iter 028 / 029, Loss: 0.400233 * Train accuracy / confusion: 79.96% / [[252, 109], [77, 490]], * Val accuracy / confusion: 72.88% / [[144, 86], [74, 286]] ------------------------------ Epoch 243 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.433089 - Iter 028 / 029, Loss: 0.448737 * Train accuracy / confusion: 80.50% / [[254, 111], [70, 493]], * Val accuracy / confusion: 76.44% / [[155, 75], [64, 296]] ------------------------------ Epoch 244 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.385664 - Iter 028 / 029, Loss: 0.317505 * Train accuracy / confusion: 80.39% / [[259, 101], [81, 487]], * Val accuracy / confusion: 71.86% / [[142, 88], [78, 282]] ------------------------------ Epoch 245 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.323833 - Iter 028 / 029, Loss: 0.390861 * Train accuracy / confusion: 79.96% / [[258, 106], [80, 484]], * Val accuracy / confusion: 74.24% / [[139, 91], [61, 299]] ------------------------------ Epoch 246 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.481756 - Iter 028 / 029, Loss: 0.437596 * Train accuracy / confusion: 79.63% / [[247, 112], [77, 492]], * Val accuracy / confusion: 73.39% / [[153, 77], [80, 280]] ------------------------------ Epoch 247 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.463495 - Iter 028 / 029, Loss: 0.356704 * Train accuracy / confusion: 80.50% / [[257, 107], [74, 490]], * Val accuracy / confusion: 73.39% / [[152, 78], [79, 281]] ------------------------------ Epoch 248 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.383554 - Iter 028 / 029, Loss: 0.570787 * Train accuracy / confusion: 79.53% / [[245, 114], [76, 493]], * Val accuracy / confusion: 74.75% / [[147, 83], [66, 294]] ------------------------------ Epoch 249 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.334536 - Iter 028 / 029, Loss: 0.401560 * Train accuracy / confusion: 81.25% / [[256, 106], [68, 498]], * Val accuracy / confusion: 73.05% / [[145, 85], [74, 286]] ------------------------------ Epoch 250 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.340309 - Iter 028 / 029, Loss: 0.279269 * Train accuracy / confusion: 79.42% / [[247, 111], [80, 490]], * Val accuracy / confusion: 71.69% / [[122, 108], [59, 301]] ------------------------------ Epoch 251 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.487567 - Iter 028 / 029, Loss: 0.482627 * Train accuracy / confusion: 78.34% / [[243, 118], [83, 484]], * Val accuracy / confusion: 74.24% / [[143, 87], [65, 295]] ------------------------------ Epoch 252 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.297203 - Iter 028 / 029, Loss: 0.620756 * Train accuracy / confusion: 78.77% / [[245, 118], [79, 486]], * Val accuracy / confusion: 71.86% / [[133, 97], [69, 291]] ------------------------------ Epoch 253 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.543327 - Iter 028 / 029, Loss: 0.444487 * Train accuracy / confusion: 78.88% / [[236, 125], [71, 496]], * Val accuracy / confusion: 71.86% / [[139, 91], [75, 285]] ------------------------------ Epoch 254 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.382633 - Iter 028 / 029, Loss: 0.553742 * Train accuracy / confusion: 80.82% / [[262, 99], [79, 488]], * Val accuracy / confusion: 73.56% / [[142, 88], [68, 292]] ------------------------------ Epoch 255 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.366754 - Iter 028 / 029, Loss: 0.395720 * Train accuracy / confusion: 81.36% / [[258, 102], [71, 497]], * Val accuracy / confusion: 72.03% / [[135, 95], [70, 290]] ------------------------------ Epoch 256 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.386414 - Iter 028 / 029, Loss: 0.476649 * Train accuracy / confusion: 78.45% / [[241, 120], [80, 487]], * Val accuracy / confusion: 74.92% / [[144, 86], [62, 298]] ------------------------------ Epoch 257 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.475235 - Iter 028 / 029, Loss: 0.490900 * Train accuracy / confusion: 80.17% / [[254, 108], [76, 490]], * Val accuracy / confusion: 73.90% / [[143, 87], [67, 293]] ------------------------------ Epoch 258 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.247871 - Iter 028 / 029, Loss: 0.428706 * Train accuracy / confusion: 79.85% / [[257, 105], [82, 484]], * Val accuracy / confusion: 73.90% / [[150, 80], [74, 286]] ------------------------------ Epoch 259 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.621706 - Iter 028 / 029, Loss: 0.530066 * Train accuracy / confusion: 81.36% / [[261, 100], [73, 494]], * Val accuracy / confusion: 72.20% / [[136, 94], [70, 290]] ------------------------------ Epoch 260 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.378972 - Iter 028 / 029, Loss: 0.524603 * Train accuracy / confusion: 80.50% / [[255, 107], [74, 492]], * Val accuracy / confusion: 72.37% / [[139, 91], [72, 288]] ------------------------------ Epoch 261 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.510336 - Iter 028 / 029, Loss: 0.600333 * Train accuracy / confusion: 80.71% / [[261, 100], [79, 488]], * Val accuracy / confusion: 72.71% / [[135, 95], [66, 294]] ------------------------------ Epoch 262 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.299710 - Iter 028 / 029, Loss: 0.309151 * Train accuracy / confusion: 80.50% / [[260, 99], [82, 487]], * Val accuracy / confusion: 72.88% / [[142, 88], [72, 288]] ------------------------------ Epoch 263 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.467291 - Iter 028 / 029, Loss: 0.445761 * Train accuracy / confusion: 80.93% / [[257, 102], [75, 494]], * Val accuracy / confusion: 73.05% / [[147, 83], [76, 284]] ------------------------------ Epoch 264 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.350944 - Iter 028 / 029, Loss: 0.520914 * Train accuracy / confusion: 80.93% / [[253, 105], [72, 498]], * Val accuracy / confusion: 71.19% / [[147, 83], [87, 273]] ------------------------------ Epoch 265 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.332456 - Iter 028 / 029, Loss: 0.398186 * Train accuracy / confusion: 78.99% / [[252, 110], [85, 481]], * Val accuracy / confusion: 73.56% / [[143, 87], [69, 291]] ------------------------------ Epoch 266 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.370604 - Iter 028 / 029, Loss: 0.645180 * Train accuracy / confusion: 79.63% / [[245, 118], [71, 494]], * Val accuracy / confusion: 73.05% / [[141, 89], [70, 290]] ------------------------------ Epoch 267 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.386330 - Iter 028 / 029, Loss: 0.442329 * Train accuracy / confusion: 78.66% / [[243, 121], [77, 487]], * Val accuracy / confusion: 72.03% / [[138, 92], [73, 287]] ------------------------------ Epoch 268 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.341554 - Iter 028 / 029, Loss: 0.330356 * Train accuracy / confusion: 81.36% / [[261, 103], [70, 494]], * Val accuracy / confusion: 74.41% / [[149, 81], [70, 290]] ------------------------------ Epoch 269 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.280589 - Iter 028 / 029, Loss: 0.532447 * Train accuracy / confusion: 80.06% / [[252, 111], [74, 491]], * Val accuracy / confusion: 73.39% / [[140, 90], [67, 293]] ------------------------------ Epoch 270 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.267592 - Iter 028 / 029, Loss: 0.580947 * Train accuracy / confusion: 80.82% / [[253, 107], [71, 497]], * Val accuracy / confusion: 75.42% / [[139, 91], [54, 306]] ------------------------------ Epoch 271 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.506930 - Iter 028 / 029, Loss: 0.704401 * Train accuracy / confusion: 79.42% / [[245, 115], [76, 492]], * Val accuracy / confusion: 72.71% / [[141, 89], [72, 288]] ------------------------------ Epoch 272 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.488725 - Iter 028 / 029, Loss: 0.397067 * Train accuracy / confusion: 79.53% / [[249, 115], [75, 489]], * Val accuracy / confusion: 74.92% / [[145, 85], [63, 297]] ------------------------------ Epoch 273 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.368496 - Iter 028 / 029, Loss: 0.367486 * Train accuracy / confusion: 79.31% / [[244, 118], [74, 492]], * Val accuracy / confusion: 74.41% / [[144, 86], [65, 295]] ------------------------------ Epoch 274 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.322247 - Iter 028 / 029, Loss: 0.622103 * Train accuracy / confusion: 79.53% / [[248, 112], [78, 490]], * Val accuracy / confusion: 71.02% / [[133, 97], [74, 286]] ------------------------------ Epoch 275 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.491364 - Iter 028 / 029, Loss: 0.356856 * Train accuracy / confusion: 78.56% / [[247, 114], [85, 482]], * Val accuracy / confusion: 74.58% / [[140, 90], [60, 300]] ------------------------------ Epoch 276 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.470173 - Iter 028 / 029, Loss: 0.367843 * Train accuracy / confusion: 78.99% / [[246, 115], [80, 487]], * Val accuracy / confusion: 74.07% / [[147, 83], [70, 290]] ------------------------------ Epoch 277 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.531834 - Iter 028 / 029, Loss: 0.437305 * Train accuracy / confusion: 80.06% / [[253, 112], [73, 490]], * Val accuracy / confusion: 73.22% / [[137, 93], [65, 295]] ------------------------------ Epoch 278 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.538604 - Iter 028 / 029, Loss: 0.502142 * Train accuracy / confusion: 80.06% / [[248, 113], [72, 495]], * Val accuracy / confusion: 73.90% / [[137, 93], [61, 299]] ------------------------------ Epoch 279 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.524242 - Iter 028 / 029, Loss: 0.409428 * Train accuracy / confusion: 80.28% / [[249, 113], [70, 496]], * Val accuracy / confusion: 73.39% / [[142, 88], [69, 291]] ------------------------------ Epoch 280 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.351514 - Iter 028 / 029, Loss: 0.313851 * Train accuracy / confusion: 80.71% / [[260, 105], [74, 489]], * Val accuracy / confusion: 73.56% / [[138, 92], [64, 296]] ------------------------------ Epoch 281 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.484459 - Iter 028 / 029, Loss: 0.336636 * Train accuracy / confusion: 79.53% / [[246, 117], [73, 492]], * Val accuracy / confusion: 74.92% / [[142, 88], [60, 300]] ------------------------------ Epoch 282 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.486621 - Iter 028 / 029, Loss: 0.469890 * Train accuracy / confusion: 78.56% / [[243, 116], [83, 486]], * Val accuracy / confusion: 74.24% / [[140, 90], [62, 298]] ------------------------------ Epoch 283 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.411789 - Iter 028 / 029, Loss: 0.344052 * Train accuracy / confusion: 78.66% / [[250, 115], [83, 480]], * Val accuracy / confusion: 72.37% / [[138, 92], [71, 289]] ------------------------------ Epoch 284 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.351503 - Iter 028 / 029, Loss: 0.472522 * Train accuracy / confusion: 80.71% / [[252, 106], [73, 497]], * Val accuracy / confusion: 74.24% / [[139, 91], [61, 299]] ------------------------------ Epoch 285 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.512797 - Iter 028 / 029, Loss: 0.341188 * Train accuracy / confusion: 81.25% / [[252, 108], [66, 502]], * Val accuracy / confusion: 73.73% / [[150, 80], [75, 285]] ------------------------------ Epoch 286 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.426661 - Iter 028 / 029, Loss: 0.393467 * Train accuracy / confusion: 81.03% / [[259, 102], [74, 493]], * Val accuracy / confusion: 73.90% / [[141, 89], [65, 295]] ------------------------------ Epoch 287 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.445883 - Iter 028 / 029, Loss: 0.407486 * Train accuracy / confusion: 79.96% / [[250, 112], [74, 492]], * Val accuracy / confusion: 74.75% / [[139, 91], [58, 302]] ------------------------------ Epoch 288 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.392769 - Iter 028 / 029, Loss: 0.321230 * Train accuracy / confusion: 81.03% / [[256, 106], [70, 496]], * Val accuracy / confusion: 75.08% / [[144, 86], [61, 299]] ------------------------------ Epoch 289 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.423570 - Iter 028 / 029, Loss: 0.362301 * Train accuracy / confusion: 80.39% / [[254, 106], [76, 492]], * Val accuracy / confusion: 72.54% / [[145, 85], [77, 283]] ------------------------------ Epoch 290 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.513767 - Iter 028 / 029, Loss: 0.464204 * Train accuracy / confusion: 79.96% / [[254, 108], [78, 488]], * Val accuracy / confusion: 73.90% / [[139, 91], [63, 297]] ------------------------------ Epoch 291 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.431384 - Iter 028 / 029, Loss: 0.681143 * Train accuracy / confusion: 80.06% / [[248, 113], [72, 495]], * Val accuracy / confusion: 72.37% / [[127, 103], [60, 300]] ------------------------------ Epoch 292 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.505968 - Iter 028 / 029, Loss: 0.408369 * Train accuracy / confusion: 81.36% / [[254, 107], [66, 501]], * Val accuracy / confusion: 73.73% / [[138, 92], [63, 297]] ------------------------------ Epoch 293 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.364634 - Iter 028 / 029, Loss: 0.473638 * Train accuracy / confusion: 80.93% / [[253, 109], [68, 498]], * Val accuracy / confusion: 74.92% / [[140, 90], [58, 302]] ------------------------------ Epoch 294 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.460724 - Iter 028 / 029, Loss: 0.565774 * Train accuracy / confusion: 80.50% / [[254, 109], [72, 493]], * Val accuracy / confusion: 71.53% / [[139, 91], [77, 283]] ------------------------------ Epoch 295 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.512318 - Iter 028 / 029, Loss: 0.666361 * Train accuracy / confusion: 80.82% / [[258, 103], [75, 492]], * Val accuracy / confusion: 73.56% / [[147, 83], [73, 287]] ------------------------------ Epoch 296 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.458033 - Iter 028 / 029, Loss: 0.387485 * Train accuracy / confusion: 80.71% / [[257, 103], [76, 492]], * Val accuracy / confusion: 72.37% / [[137, 93], [70, 290]] ------------------------------ Epoch 297 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.429127 - Iter 028 / 029, Loss: 0.450515 * Train accuracy / confusion: 80.17% / [[246, 114], [70, 498]], * Val accuracy / confusion: 71.53% / [[148, 82], [86, 274]] ------------------------------ Epoch 298 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.474242 - Iter 028 / 029, Loss: 0.493947 * Train accuracy / confusion: 79.85% / [[248, 114], [73, 493]], * Val accuracy / confusion: 73.22% / [[133, 97], [61, 299]] ------------------------------ Epoch 299 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.586320 - Iter 028 / 029, Loss: 0.322967 * Train accuracy / confusion: 80.17% / [[255, 109], [75, 489]], * Val accuracy / confusion: 73.73% / [[152, 78], [77, 283]] ------------------------------ Epoch 300 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.473616 - Iter 028 / 029, Loss: 0.536935 * Train accuracy / confusion: 79.96% / [[257, 104], [82, 485]], * Val accuracy / confusion: 73.73% / [[147, 83], [72, 288]] ------------------------------ Epoch 301 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.432824 - Iter 028 / 029, Loss: 0.538570 * Train accuracy / confusion: 80.06% / [[250, 113], [72, 493]], * Val accuracy / confusion: 73.22% / [[137, 93], [65, 295]] ------------------------------ Epoch 302 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.425786 - Iter 028 / 029, Loss: 0.347920 * Train accuracy / confusion: 79.85% / [[247, 117], [70, 494]], * Val accuracy / confusion: 74.41% / [[142, 88], [63, 297]] ------------------------------ Epoch 303 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.314569 - Iter 028 / 029, Loss: 0.565928 * Train accuracy / confusion: 80.82% / [[256, 106], [72, 494]], * Val accuracy / confusion: 74.41% / [[145, 85], [66, 294]] ------------------------------ Epoch 304 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.387842 - Iter 028 / 029, Loss: 0.334442 * Train accuracy / confusion: 81.14% / [[261, 103], [72, 492]], * Val accuracy / confusion: 73.90% / [[140, 90], [64, 296]] ------------------------------ Epoch 305 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.591995 - Iter 028 / 029, Loss: 0.455837 * Train accuracy / confusion: 80.39% / [[257, 105], [77, 489]], * Val accuracy / confusion: 72.54% / [[126, 104], [58, 302]] ------------------------------ Epoch 306 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.310447 - Iter 028 / 029, Loss: 0.329027 * Train accuracy / confusion: 80.93% / [[262, 103], [74, 489]], * Val accuracy / confusion: 71.02% / [[146, 84], [87, 273]] ------------------------------ Epoch 307 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.459914 - Iter 028 / 029, Loss: 0.380075 * Train accuracy / confusion: 80.17% / [[252, 109], [75, 492]], * Val accuracy / confusion: 74.75% / [[147, 83], [66, 294]] ------------------------------ Epoch 308 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.452803 - Iter 028 / 029, Loss: 0.409771 * Train accuracy / confusion: 82.11% / [[254, 106], [60, 508]], * Val accuracy / confusion: 73.22% / [[141, 89], [69, 291]] ------------------------------ Epoch 309 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.603380 - Iter 028 / 029, Loss: 0.350560 * Train accuracy / confusion: 80.06% / [[255, 109], [76, 488]], * Val accuracy / confusion: 71.86% / [[148, 82], [84, 276]] ------------------------------ Epoch 310 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.429295 - Iter 028 / 029, Loss: 0.469361 * Train accuracy / confusion: 80.06% / [[251, 111], [74, 492]], * Val accuracy / confusion: 73.39% / [[138, 92], [65, 295]] ------------------------------ Epoch 311 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.281730 - Iter 028 / 029, Loss: 0.652853 * Train accuracy / confusion: 79.85% / [[248, 113], [74, 493]], * Val accuracy / confusion: 72.54% / [[134, 96], [66, 294]] ------------------------------ Epoch 312 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.372669 - Iter 028 / 029, Loss: 0.494972 * Train accuracy / confusion: 80.60% / [[250, 110], [70, 498]], * Val accuracy / confusion: 71.19% / [[128, 102], [68, 292]] ------------------------------ Epoch 313 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.414587 - Iter 028 / 029, Loss: 0.338154 * Train accuracy / confusion: 79.96% / [[245, 113], [73, 497]], * Val accuracy / confusion: 72.03% / [[139, 91], [74, 286]] ------------------------------ Epoch 314 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.496476 - Iter 028 / 029, Loss: 0.306083 * Train accuracy / confusion: 79.96% / [[255, 103], [83, 487]], * Val accuracy / confusion: 73.05% / [[142, 88], [71, 289]] ------------------------------ Epoch 315 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.474308 - Iter 028 / 029, Loss: 0.345296 * Train accuracy / confusion: 80.50% / [[252, 109], [72, 495]], * Val accuracy / confusion: 74.07% / [[138, 92], [61, 299]] ------------------------------ Epoch 316 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.252405 - Iter 028 / 029, Loss: 0.391063 * Train accuracy / confusion: 80.93% / [[256, 105], [72, 495]], * Val accuracy / confusion: 73.22% / [[140, 90], [68, 292]] ------------------------------ Epoch 317 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.540062 - Iter 028 / 029, Loss: 0.389162 * Train accuracy / confusion: 80.28% / [[254, 108], [75, 491]], * Val accuracy / confusion: 74.24% / [[138, 92], [60, 300]] ------------------------------ Epoch 318 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.376334 - Iter 028 / 029, Loss: 0.455256 * Train accuracy / confusion: 80.71% / [[252, 112], [67, 497]], * Val accuracy / confusion: 74.07% / [[145, 85], [68, 292]] ------------------------------ Epoch 319 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.607340 - Iter 028 / 029, Loss: 0.541921 * Train accuracy / confusion: 80.39% / [[254, 112], [70, 492]], * Val accuracy / confusion: 72.71% / [[135, 95], [66, 294]] ------------------------------ Epoch 320 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.309544 - Iter 028 / 029, Loss: 0.649951 * Train accuracy / confusion: 80.71% / [[257, 109], [70, 492]], * Val accuracy / confusion: 73.22% / [[149, 81], [77, 283]] ------------------------------ Epoch 321 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.435107 - Iter 028 / 029, Loss: 0.324093 * Train accuracy / confusion: 80.28% / [[245, 116], [67, 500]], * Val accuracy / confusion: 72.71% / [[141, 89], [72, 288]] ------------------------------ Epoch 322 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.297217 - Iter 028 / 029, Loss: 0.564432 * Train accuracy / confusion: 81.47% / [[248, 111], [61, 508]], * Val accuracy / confusion: 73.05% / [[140, 90], [69, 291]] ------------------------------ Epoch 323 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.384585 - Iter 028 / 029, Loss: 0.405099 * Train accuracy / confusion: 79.74% / [[256, 107], [81, 484]], * Val accuracy / confusion: 74.75% / [[138, 92], [57, 303]] ------------------------------ Epoch 324 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.519145 - Iter 028 / 029, Loss: 0.358968 * Train accuracy / confusion: 80.06% / [[257, 103], [82, 486]], * Val accuracy / confusion: 73.22% / [[147, 83], [75, 285]] ------------------------------ Epoch 325 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.477620 - Iter 028 / 029, Loss: 0.569975 * Train accuracy / confusion: 80.93% / [[260, 104], [73, 491]], * Val accuracy / confusion: 74.41% / [[140, 90], [61, 299]] ------------------------------ Epoch 326 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.378435 - Iter 028 / 029, Loss: 0.312897 * Train accuracy / confusion: 80.28% / [[251, 113], [70, 494]], * Val accuracy / confusion: 72.20% / [[136, 94], [70, 290]] ------------------------------ Epoch 327 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.477736 - Iter 028 / 029, Loss: 0.471386 * Train accuracy / confusion: 80.06% / [[259, 102], [83, 484]], * Val accuracy / confusion: 73.22% / [[145, 85], [73, 287]] ------------------------------ Epoch 328 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.567913 - Iter 028 / 029, Loss: 0.510310 * Train accuracy / confusion: 81.14% / [[259, 105], [70, 494]], * Val accuracy / confusion: 74.75% / [[145, 85], [64, 296]] ------------------------------ Epoch 329 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.451940 - Iter 028 / 029, Loss: 0.402486 * Train accuracy / confusion: 81.47% / [[261, 100], [72, 495]], * Val accuracy / confusion: 73.90% / [[153, 77], [77, 283]] ------------------------------ Epoch 330 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.321260 - Iter 028 / 029, Loss: 0.497948 * Train accuracy / confusion: 79.20% / [[239, 120], [73, 496]], * Val accuracy / confusion: 73.73% / [[142, 88], [67, 293]] ------------------------------ Epoch 331 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.407345 - Iter 028 / 029, Loss: 0.523048 * Train accuracy / confusion: 80.17% / [[254, 110], [74, 490]], * Val accuracy / confusion: 73.56% / [[129, 101], [55, 305]] ------------------------------ Epoch 332 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.445758 - Iter 028 / 029, Loss: 0.490692 * Train accuracy / confusion: 80.39% / [[243, 116], [66, 503]], * Val accuracy / confusion: 74.24% / [[137, 93], [59, 301]] ------------------------------ Epoch 333 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.432394 - Iter 028 / 029, Loss: 0.441227 * Train accuracy / confusion: 81.25% / [[250, 112], [62, 504]], * Val accuracy / confusion: 72.20% / [[139, 91], [73, 287]] ------------------------------ Epoch 334 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.386025 - Iter 028 / 029, Loss: 0.375517 * Train accuracy / confusion: 81.36% / [[261, 103], [70, 494]], * Val accuracy / confusion: 72.03% / [[137, 93], [72, 288]] ------------------------------ Epoch 335 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.481276 - Iter 028 / 029, Loss: 0.479307 * Train accuracy / confusion: 81.90% / [[262, 103], [65, 498]], * Val accuracy / confusion: 72.71% / [[137, 93], [68, 292]] ------------------------------ Epoch 336 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.350357 - Iter 028 / 029, Loss: 0.403152 * Train accuracy / confusion: 81.14% / [[258, 106], [69, 495]], * Val accuracy / confusion: 72.88% / [[139, 91], [69, 291]] ------------------------------ Epoch 337 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.351439 - Iter 028 / 029, Loss: 0.418721 * Train accuracy / confusion: 80.28% / [[250, 114], [69, 495]], * Val accuracy / confusion: 73.39% / [[138, 92], [65, 295]] ------------------------------ Epoch 338 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.313096 - Iter 028 / 029, Loss: 0.587852 * Train accuracy / confusion: 82.11% / [[258, 100], [66, 504]], * Val accuracy / confusion: 71.53% / [[142, 88], [80, 280]] ------------------------------ Epoch 339 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.414005 - Iter 028 / 029, Loss: 0.350602 * Train accuracy / confusion: 82.11% / [[259, 96], [70, 503]], * Val accuracy / confusion: 69.83% / [[146, 84], [94, 266]] ------------------------------ Epoch 340 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.609224 - Iter 028 / 029, Loss: 0.275876 * Train accuracy / confusion: 80.39% / [[249, 107], [75, 497]], * Val accuracy / confusion: 75.76% / [[152, 78], [65, 295]] ------------------------------ Epoch 341 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.784430 - Iter 028 / 029, Loss: 0.397234 * Train accuracy / confusion: 79.74% / [[249, 113], [75, 491]], * Val accuracy / confusion: 74.07% / [[138, 92], [61, 299]] ------------------------------ Epoch 342 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.374082 - Iter 028 / 029, Loss: 0.446174 * Train accuracy / confusion: 81.14% / [[256, 106], [69, 497]], * Val accuracy / confusion: 71.69% / [[136, 94], [73, 287]] ------------------------------ Epoch 343 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.411073 - Iter 028 / 029, Loss: 0.343512 * Train accuracy / confusion: 81.47% / [[250, 113], [59, 506]], * Val accuracy / confusion: 75.93% / [[153, 77], [65, 295]] ------------------------------ Epoch 344 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.513998 - Iter 028 / 029, Loss: 0.414002 * Train accuracy / confusion: 80.60% / [[258, 102], [78, 490]], * Val accuracy / confusion: 75.25% / [[148, 82], [64, 296]] ------------------------------ Epoch 345 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.370750 - Iter 028 / 029, Loss: 0.436127 * Train accuracy / confusion: 80.71% / [[256, 106], [73, 493]], * Val accuracy / confusion: 72.54% / [[135, 95], [67, 293]] ------------------------------ Epoch 346 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.465313 - Iter 028 / 029, Loss: 0.638439 * Train accuracy / confusion: 81.25% / [[251, 108], [66, 503]], * Val accuracy / confusion: 74.58% / [[151, 79], [71, 289]] ------------------------------ Epoch 347 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.366289 - Iter 028 / 029, Loss: 0.608990 * Train accuracy / confusion: 79.09% / [[251, 112], [82, 483]], * Val accuracy / confusion: 73.39% / [[145, 85], [72, 288]] ------------------------------ Epoch 348 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.442725 - Iter 028 / 029, Loss: 0.564907 * Train accuracy / confusion: 81.47% / [[264, 99], [73, 492]], * Val accuracy / confusion: 74.07% / [[151, 79], [74, 286]] ------------------------------ Epoch 349 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.306076 - Iter 028 / 029, Loss: 0.372964 * Train accuracy / confusion: 82.33% / [[265, 99], [65, 499]], * Val accuracy / confusion: 72.37% / [[139, 91], [72, 288]] ------------------------------ Epoch 350 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.398925 - Iter 028 / 029, Loss: 0.575495 * Train accuracy / confusion: 81.47% / [[255, 106], [66, 501]], * Val accuracy / confusion: 73.22% / [[133, 97], [61, 299]] ------------------------------ Epoch 351 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.407483 - Iter 028 / 029, Loss: 0.610189 * Train accuracy / confusion: 80.39% / [[246, 114], [68, 500]], * Val accuracy / confusion: 74.75% / [[140, 90], [59, 301]] ------------------------------ Epoch 352 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.399103 - Iter 028 / 029, Loss: 0.396081 * Train accuracy / confusion: 80.82% / [[253, 110], [68, 497]], * Val accuracy / confusion: 73.39% / [[144, 86], [71, 289]] ------------------------------ Epoch 353 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.446373 - Iter 028 / 029, Loss: 0.609170 * Train accuracy / confusion: 80.82% / [[260, 103], [75, 490]], * Val accuracy / confusion: 75.42% / [[139, 91], [54, 306]] ------------------------------ Epoch 354 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.439685 - Iter 028 / 029, Loss: 0.524685 * Train accuracy / confusion: 81.25% / [[256, 106], [68, 498]], * Val accuracy / confusion: 74.24% / [[139, 91], [61, 299]] ------------------------------ Epoch 355 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.324542 - Iter 028 / 029, Loss: 0.312864 * Train accuracy / confusion: 80.82% / [[261, 104], [74, 489]], * Val accuracy / confusion: 74.58% / [[141, 89], [61, 299]] ------------------------------ Epoch 356 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.289350 - Iter 028 / 029, Loss: 0.440722 * Train accuracy / confusion: 80.71% / [[255, 108], [71, 494]], * Val accuracy / confusion: 73.56% / [[147, 83], [73, 287]] ------------------------------ Epoch 357 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.430205 - Iter 028 / 029, Loss: 0.622539 * Train accuracy / confusion: 81.57% / [[259, 102], [69, 498]], * Val accuracy / confusion: 75.42% / [[144, 86], [59, 301]] ------------------------------ Epoch 358 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.392471 - Iter 028 / 029, Loss: 0.448135 * Train accuracy / confusion: 81.47% / [[249, 112], [60, 507]], * Val accuracy / confusion: 73.39% / [[143, 87], [70, 290]] ------------------------------ Epoch 359 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.460306 - Iter 028 / 029, Loss: 0.479533 * Train accuracy / confusion: 81.90% / [[257, 106], [62, 503]], * Val accuracy / confusion: 72.20% / [[132, 98], [66, 294]] ------------------------------ Epoch 360 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.425826 - Iter 028 / 029, Loss: 0.558462 * Train accuracy / confusion: 81.57% / [[257, 101], [70, 500]], * Val accuracy / confusion: 71.53% / [[134, 96], [72, 288]] ------------------------------ Epoch 361 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.416061 - Iter 028 / 029, Loss: 0.401901 * Train accuracy / confusion: 80.39% / [[257, 109], [73, 489]], * Val accuracy / confusion: 72.37% / [[129, 101], [62, 298]] ------------------------------ Epoch 362 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.505103 - Iter 028 / 029, Loss: 0.473280 * Train accuracy / confusion: 80.93% / [[255, 106], [71, 496]], * Val accuracy / confusion: 73.22% / [[135, 95], [63, 297]] ------------------------------ Epoch 363 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.331100 - Iter 028 / 029, Loss: 0.276938 * Train accuracy / confusion: 81.25% / [[253, 107], [67, 501]], * Val accuracy / confusion: 75.25% / [[142, 88], [58, 302]] ------------------------------ Epoch 364 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.516099 - Iter 028 / 029, Loss: 0.368274 * Train accuracy / confusion: 81.36% / [[258, 103], [70, 497]], * Val accuracy / confusion: 74.07% / [[146, 84], [69, 291]] ------------------------------ Epoch 365 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.348175 - Iter 028 / 029, Loss: 0.397396 * Train accuracy / confusion: 81.25% / [[257, 105], [69, 497]], * Val accuracy / confusion: 75.42% / [[148, 82], [63, 297]] ------------------------------ Epoch 366 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.376165 - Iter 028 / 029, Loss: 0.426046 * Train accuracy / confusion: 80.60% / [[259, 103], [77, 489]], * Val accuracy / confusion: 74.07% / [[146, 84], [69, 291]] ------------------------------ Epoch 367 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.340319 - Iter 028 / 029, Loss: 0.352809 * Train accuracy / confusion: 81.03% / [[252, 109], [67, 500]], * Val accuracy / confusion: 72.54% / [[131, 99], [63, 297]] ------------------------------ Epoch 368 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.466375 - Iter 028 / 029, Loss: 0.354616 * Train accuracy / confusion: 80.50% / [[259, 99], [82, 488]], * Val accuracy / confusion: 75.59% / [[153, 77], [67, 293]] ------------------------------ Epoch 369 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.524517 - Iter 028 / 029, Loss: 0.424664 * Train accuracy / confusion: 81.68% / [[264, 101], [69, 494]], * Val accuracy / confusion: 74.58% / [[148, 82], [68, 292]] ------------------------------ Epoch 370 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.502835 - Iter 028 / 029, Loss: 0.332831 * Train accuracy / confusion: 79.96% / [[246, 116], [70, 496]], * Val accuracy / confusion: 74.07% / [[139, 91], [62, 298]] ------------------------------ Epoch 371 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.442894 - Iter 028 / 029, Loss: 0.279792 * Train accuracy / confusion: 80.06% / [[251, 113], [72, 492]], * Val accuracy / confusion: 71.69% / [[123, 107], [60, 300]] ------------------------------ Epoch 372 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.301580 - Iter 028 / 029, Loss: 0.511785 * Train accuracy / confusion: 79.31% / [[247, 113], [79, 489]], * Val accuracy / confusion: 75.08% / [[154, 76], [71, 289]] ------------------------------ Epoch 373 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.463806 - Iter 028 / 029, Loss: 0.498524 * Train accuracy / confusion: 81.03% / [[251, 105], [71, 501]], * Val accuracy / confusion: 72.54% / [[134, 96], [66, 294]] ------------------------------ Epoch 374 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.379429 - Iter 028 / 029, Loss: 0.338456 * Train accuracy / confusion: 81.68% / [[255, 103], [67, 503]], * Val accuracy / confusion: 74.07% / [[156, 74], [79, 281]] ------------------------------ Epoch 375 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.372325 - Iter 028 / 029, Loss: 0.579463 * Train accuracy / confusion: 80.39% / [[253, 108], [74, 493]], * Val accuracy / confusion: 71.53% / [[137, 93], [75, 285]] ------------------------------ Epoch 376 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.357617 - Iter 028 / 029, Loss: 0.288547 * Train accuracy / confusion: 81.36% / [[258, 102], [71, 497]], * Val accuracy / confusion: 74.75% / [[154, 76], [73, 287]] ------------------------------ Epoch 377 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.558527 - Iter 028 / 029, Loss: 0.367416 * Train accuracy / confusion: 81.36% / [[253, 109], [64, 502]], * Val accuracy / confusion: 74.75% / [[148, 82], [67, 293]] ------------------------------ Epoch 378 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.350033 - Iter 028 / 029, Loss: 0.374201 * Train accuracy / confusion: 78.77% / [[245, 116], [81, 486]], * Val accuracy / confusion: 73.39% / [[140, 90], [67, 293]] ------------------------------ Epoch 379 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.451124 - Iter 028 / 029, Loss: 0.321621 * Train accuracy / confusion: 80.60% / [[256, 102], [78, 492]], * Val accuracy / confusion: 75.08% / [[141, 89], [58, 302]] ------------------------------ Epoch 380 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.416704 - Iter 028 / 029, Loss: 0.338862 * Train accuracy / confusion: 82.54% / [[257, 103], [59, 509]], * Val accuracy / confusion: 75.42% / [[145, 85], [60, 300]] ------------------------------ Epoch 381 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.542625 - Iter 028 / 029, Loss: 0.407983 * Train accuracy / confusion: 79.74% / [[258, 106], [82, 482]], * Val accuracy / confusion: 75.93% / [[147, 83], [59, 301]] ------------------------------ Epoch 382 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.365363 - Iter 028 / 029, Loss: 0.583327 * Train accuracy / confusion: 80.82% / [[255, 107], [71, 495]], * Val accuracy / confusion: 74.24% / [[147, 83], [69, 291]] ------------------------------ Epoch 383 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.535809 - Iter 028 / 029, Loss: 0.382510 * Train accuracy / confusion: 81.36% / [[256, 104], [69, 499]], * Val accuracy / confusion: 73.39% / [[142, 88], [69, 291]] ------------------------------ Epoch 384 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.503219 - Iter 028 / 029, Loss: 0.328745 * Train accuracy / confusion: 82.65% / [[268, 91], [70, 499]], * Val accuracy / confusion: 74.58% / [[140, 90], [60, 300]] ------------------------------ Epoch 385 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.393902 - Iter 028 / 029, Loss: 0.460136 * Train accuracy / confusion: 80.71% / [[255, 107], [72, 494]], * Val accuracy / confusion: 73.90% / [[148, 82], [72, 288]] ------------------------------ Epoch 386 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.477231 - Iter 028 / 029, Loss: 0.386878 * Train accuracy / confusion: 82.44% / [[259, 100], [63, 506]], * Val accuracy / confusion: 72.88% / [[134, 96], [64, 296]] ------------------------------ Epoch 387 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.467829 - Iter 028 / 029, Loss: 0.614416 * Train accuracy / confusion: 80.50% / [[256, 106], [75, 491]], * Val accuracy / confusion: 71.86% / [[128, 102], [64, 296]] ------------------------------ Epoch 388 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.346433 - Iter 028 / 029, Loss: 0.397111 * Train accuracy / confusion: 79.85% / [[252, 110], [77, 489]], * Val accuracy / confusion: 73.39% / [[141, 89], [68, 292]] ------------------------------ Epoch 389 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.292440 - Iter 028 / 029, Loss: 0.477571 * Train accuracy / confusion: 81.79% / [[264, 99], [70, 495]], * Val accuracy / confusion: 74.07% / [[146, 84], [69, 291]] ------------------------------ Epoch 390 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.464633 - Iter 028 / 029, Loss: 0.588122 * Train accuracy / confusion: 82.00% / [[259, 102], [65, 502]], * Val accuracy / confusion: 74.41% / [[129, 101], [50, 310]] ------------------------------ Epoch 391 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.426506 - Iter 028 / 029, Loss: 0.609985 * Train accuracy / confusion: 81.36% / [[259, 106], [67, 496]], * Val accuracy / confusion: 73.56% / [[148, 82], [74, 286]] ------------------------------ Epoch 392 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.516662 - Iter 028 / 029, Loss: 0.351355 * Train accuracy / confusion: 82.11% / [[264, 97], [69, 498]], * Val accuracy / confusion: 72.88% / [[144, 86], [74, 286]] ------------------------------ Epoch 393 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.274696 - Iter 028 / 029, Loss: 0.470040 * Train accuracy / confusion: 82.44% / [[267, 95], [68, 498]], * Val accuracy / confusion: 73.56% / [[156, 74], [82, 278]] ------------------------------ Epoch 394 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.370194 - Iter 028 / 029, Loss: 0.430226 * Train accuracy / confusion: 81.14% / [[254, 107], [68, 499]], * Val accuracy / confusion: 74.92% / [[150, 80], [68, 292]] ------------------------------ Epoch 395 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.461928 - Iter 028 / 029, Loss: 0.470170 * Train accuracy / confusion: 80.82% / [[260, 99], [79, 490]], * Val accuracy / confusion: 74.07% / [[134, 96], [57, 303]] ------------------------------ Epoch 396 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.362884 - Iter 028 / 029, Loss: 0.407856 * Train accuracy / confusion: 82.00% / [[261, 104], [63, 500]], * Val accuracy / confusion: 72.88% / [[129, 101], [59, 301]] ------------------------------ Epoch 397 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.275957 - Iter 028 / 029, Loss: 0.355648 * Train accuracy / confusion: 80.50% / [[257, 105], [76, 490]], * Val accuracy / confusion: 73.90% / [[142, 88], [66, 294]] ------------------------------ Epoch 398 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.416651 - Iter 028 / 029, Loss: 0.312933 * Train accuracy / confusion: 80.28% / [[256, 107], [76, 489]], * Val accuracy / confusion: 73.22% / [[136, 94], [64, 296]] ------------------------------ Epoch 399 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.380822 - Iter 028 / 029, Loss: 0.511717 * Train accuracy / confusion: 80.82% / [[254, 109], [69, 496]], * Val accuracy / confusion: 74.07% / [[131, 99], [54, 306]] ------------------------------ Epoch 400 / 500, Learning rate: 1.92e-04 ------------------------------ - Iter 014 / 029, Loss: 0.382955 - Iter 028 / 029, Loss: 0.348450 * Train accuracy / confusion: 81.79% / [[261, 98], [71, 498]], * Val accuracy / confusion: 75.25% / [[152, 78], [68, 292]] ------------------------------ Epoch 401 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.336350 - Iter 028 / 029, Loss: 0.370183 * Train accuracy / confusion: 82.11% / [[258, 102], [64, 504]], * Val accuracy / confusion: 74.75% / [[148, 82], [67, 293]] ------------------------------ Epoch 402 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.421328 - Iter 028 / 029, Loss: 0.406207 * Train accuracy / confusion: 79.85% / [[250, 114], [73, 491]], * Val accuracy / confusion: 73.22% / [[139, 91], [67, 293]] ------------------------------ Epoch 403 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.452431 - Iter 028 / 029, Loss: 0.476947 * Train accuracy / confusion: 81.14% / [[255, 110], [65, 498]], * Val accuracy / confusion: 73.56% / [[145, 85], [71, 289]] ------------------------------ Epoch 404 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.553239 - Iter 028 / 029, Loss: 0.528363 * Train accuracy / confusion: 82.33% / [[256, 108], [56, 508]], * Val accuracy / confusion: 74.58% / [[138, 92], [58, 302]] ------------------------------ Epoch 405 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.574160 - Iter 028 / 029, Loss: 0.336401 * Train accuracy / confusion: 80.82% / [[250, 109], [69, 500]], * Val accuracy / confusion: 75.08% / [[144, 86], [61, 299]] ------------------------------ Epoch 406 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.308610 - Iter 028 / 029, Loss: 0.328319 * Train accuracy / confusion: 80.71% / [[251, 106], [73, 498]], * Val accuracy / confusion: 72.37% / [[149, 81], [82, 278]] ------------------------------ Epoch 407 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.328367 - Iter 028 / 029, Loss: 0.485884 * Train accuracy / confusion: 82.00% / [[257, 104], [63, 504]], * Val accuracy / confusion: 70.68% / [[139, 91], [82, 278]] ------------------------------ Epoch 408 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.433647 - Iter 028 / 029, Loss: 0.380590 * Train accuracy / confusion: 80.93% / [[261, 104], [73, 490]], * Val accuracy / confusion: 72.71% / [[133, 97], [64, 296]] ------------------------------ Epoch 409 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.507181 - Iter 028 / 029, Loss: 0.277618 * Train accuracy / confusion: 82.76% / [[262, 100], [60, 506]], * Val accuracy / confusion: 73.39% / [[141, 89], [68, 292]] ------------------------------ Epoch 410 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.339507 - Iter 028 / 029, Loss: 0.508032 * Train accuracy / confusion: 80.71% / [[252, 108], [71, 497]], * Val accuracy / confusion: 74.41% / [[141, 89], [62, 298]] ------------------------------ Epoch 411 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.407391 - Iter 028 / 029, Loss: 0.295338 * Train accuracy / confusion: 79.42% / [[252, 109], [82, 485]], * Val accuracy / confusion: 73.22% / [[139, 91], [67, 293]] ------------------------------ Epoch 412 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.467534 - Iter 028 / 029, Loss: 0.370917 * Train accuracy / confusion: 80.17% / [[254, 109], [75, 490]], * Val accuracy / confusion: 74.07% / [[137, 93], [60, 300]] ------------------------------ Epoch 413 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.412239 - Iter 028 / 029, Loss: 0.341872 * Train accuracy / confusion: 82.33% / [[271, 94], [70, 493]], * Val accuracy / confusion: 74.07% / [[142, 88], [65, 295]] ------------------------------ Epoch 414 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.353238 - Iter 028 / 029, Loss: 0.410597 * Train accuracy / confusion: 81.90% / [[253, 107], [61, 507]], * Val accuracy / confusion: 73.73% / [[146, 84], [71, 289]] ------------------------------ Epoch 415 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.437701 - Iter 028 / 029, Loss: 0.457419 * Train accuracy / confusion: 81.47% / [[260, 101], [71, 496]], * Val accuracy / confusion: 73.22% / [[137, 93], [65, 295]] ------------------------------ Epoch 416 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.439833 - Iter 028 / 029, Loss: 0.399539 * Train accuracy / confusion: 79.53% / [[254, 104], [86, 484]], * Val accuracy / confusion: 75.25% / [[144, 86], [60, 300]] ------------------------------ Epoch 417 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.293895 - Iter 028 / 029, Loss: 0.332623 * Train accuracy / confusion: 80.28% / [[254, 109], [74, 491]], * Val accuracy / confusion: 73.39% / [[145, 85], [72, 288]] ------------------------------ Epoch 418 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.364197 - Iter 028 / 029, Loss: 0.421522 * Train accuracy / confusion: 80.60% / [[249, 109], [71, 499]], * Val accuracy / confusion: 73.05% / [[143, 87], [72, 288]] ------------------------------ Epoch 419 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.439089 - Iter 028 / 029, Loss: 0.490299 * Train accuracy / confusion: 81.03% / [[257, 106], [70, 495]], * Val accuracy / confusion: 74.07% / [[141, 89], [64, 296]] ------------------------------ Epoch 420 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.582698 - Iter 028 / 029, Loss: 0.519990 * Train accuracy / confusion: 80.82% / [[259, 102], [76, 491]], * Val accuracy / confusion: 72.54% / [[136, 94], [68, 292]] ------------------------------ Epoch 421 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.334754 - Iter 028 / 029, Loss: 0.435656 * Train accuracy / confusion: 81.47% / [[262, 103], [69, 494]], * Val accuracy / confusion: 74.75% / [[140, 90], [59, 301]] ------------------------------ Epoch 422 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.447568 - Iter 028 / 029, Loss: 0.300743 * Train accuracy / confusion: 82.44% / [[265, 97], [66, 500]], * Val accuracy / confusion: 73.56% / [[142, 88], [68, 292]] ------------------------------ Epoch 423 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.607249 - Iter 028 / 029, Loss: 0.550496 * Train accuracy / confusion: 80.39% / [[252, 108], [74, 494]], * Val accuracy / confusion: 74.07% / [[151, 79], [74, 286]] ------------------------------ Epoch 424 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.439514 - Iter 028 / 029, Loss: 0.383287 * Train accuracy / confusion: 80.39% / [[250, 116], [66, 496]], * Val accuracy / confusion: 75.59% / [[153, 77], [67, 293]] ------------------------------ Epoch 425 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.337423 - Iter 028 / 029, Loss: 0.395575 * Train accuracy / confusion: 81.36% / [[262, 103], [70, 493]], * Val accuracy / confusion: 73.39% / [[148, 82], [75, 285]] ------------------------------ Epoch 426 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.272637 - Iter 028 / 029, Loss: 0.256054 * Train accuracy / confusion: 80.93% / [[257, 107], [70, 494]], * Val accuracy / confusion: 74.75% / [[138, 92], [57, 303]] ------------------------------ Epoch 427 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.507362 - Iter 028 / 029, Loss: 0.563015 * Train accuracy / confusion: 83.30% / [[268, 94], [61, 505]], * Val accuracy / confusion: 74.24% / [[142, 88], [64, 296]] ------------------------------ Epoch 428 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.469850 - Iter 028 / 029, Loss: 0.637719 * Train accuracy / confusion: 80.39% / [[263, 101], [81, 483]], * Val accuracy / confusion: 75.59% / [[149, 81], [63, 297]] ------------------------------ Epoch 429 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.519848 - Iter 028 / 029, Loss: 0.358673 * Train accuracy / confusion: 82.54% / [[260, 103], [59, 506]], * Val accuracy / confusion: 74.41% / [[144, 86], [65, 295]] ------------------------------ Epoch 430 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.463943 - Iter 028 / 029, Loss: 0.400720 * Train accuracy / confusion: 79.85% / [[251, 111], [76, 490]], * Val accuracy / confusion: 72.88% / [[134, 96], [64, 296]] ------------------------------ Epoch 431 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.518387 - Iter 028 / 029, Loss: 0.626717 * Train accuracy / confusion: 80.50% / [[247, 114], [67, 500]], * Val accuracy / confusion: 75.25% / [[147, 83], [63, 297]] ------------------------------ Epoch 432 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.498379 - Iter 028 / 029, Loss: 0.278479 * Train accuracy / confusion: 81.79% / [[263, 97], [72, 496]], * Val accuracy / confusion: 75.08% / [[144, 86], [61, 299]] ------------------------------ Epoch 433 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.349040 - Iter 028 / 029, Loss: 0.350075 * Train accuracy / confusion: 81.36% / [[259, 104], [69, 496]], * Val accuracy / confusion: 73.73% / [[135, 95], [60, 300]] ------------------------------ Epoch 434 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.358778 - Iter 028 / 029, Loss: 0.436202 * Train accuracy / confusion: 81.68% / [[265, 98], [72, 493]], * Val accuracy / confusion: 73.05% / [[135, 95], [64, 296]] ------------------------------ Epoch 435 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.461162 - Iter 028 / 029, Loss: 0.554700 * Train accuracy / confusion: 80.06% / [[256, 106], [79, 487]], * Val accuracy / confusion: 75.08% / [[150, 80], [67, 293]] ------------------------------ Epoch 436 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.532302 - Iter 028 / 029, Loss: 0.395501 * Train accuracy / confusion: 81.36% / [[263, 96], [77, 492]], * Val accuracy / confusion: 72.88% / [[142, 88], [72, 288]] ------------------------------ Epoch 437 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.377444 - Iter 028 / 029, Loss: 0.353891 * Train accuracy / confusion: 81.57% / [[263, 98], [73, 494]], * Val accuracy / confusion: 73.73% / [[147, 83], [72, 288]] ------------------------------ Epoch 438 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.367616 - Iter 028 / 029, Loss: 0.539807 * Train accuracy / confusion: 82.65% / [[267, 93], [68, 500]], * Val accuracy / confusion: 73.39% / [[138, 92], [65, 295]] ------------------------------ Epoch 439 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.402374 - Iter 028 / 029, Loss: 0.523535 * Train accuracy / confusion: 80.60% / [[255, 106], [74, 493]], * Val accuracy / confusion: 74.24% / [[143, 87], [65, 295]] ------------------------------ Epoch 440 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.300559 - Iter 028 / 029, Loss: 0.452561 * Train accuracy / confusion: 81.47% / [[260, 104], [68, 496]], * Val accuracy / confusion: 71.69% / [[129, 101], [66, 294]] ------------------------------ Epoch 441 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.342821 - Iter 028 / 029, Loss: 0.516409 * Train accuracy / confusion: 82.33% / [[259, 104], [60, 505]], * Val accuracy / confusion: 75.42% / [[147, 83], [62, 298]] ------------------------------ Epoch 442 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.478125 - Iter 028 / 029, Loss: 0.426852 * Train accuracy / confusion: 80.71% / [[256, 104], [75, 493]], * Val accuracy / confusion: 72.88% / [[141, 89], [71, 289]] ------------------------------ Epoch 443 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.478191 - Iter 028 / 029, Loss: 0.470948 * Train accuracy / confusion: 80.60% / [[258, 106], [74, 490]], * Val accuracy / confusion: 75.42% / [[138, 92], [53, 307]] ------------------------------ Epoch 444 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.607628 - Iter 028 / 029, Loss: 0.433143 * Train accuracy / confusion: 81.36% / [[259, 106], [67, 496]], * Val accuracy / confusion: 74.92% / [[139, 91], [57, 303]] ------------------------------ Epoch 445 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.284105 - Iter 028 / 029, Loss: 0.552317 * Train accuracy / confusion: 82.33% / [[262, 102], [62, 502]], * Val accuracy / confusion: 74.24% / [[151, 79], [73, 287]] ------------------------------ Epoch 446 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.461810 - Iter 028 / 029, Loss: 0.444652 * Train accuracy / confusion: 81.90% / [[267, 96], [72, 493]], * Val accuracy / confusion: 72.71% / [[142, 88], [73, 287]] ------------------------------ Epoch 447 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.467007 - Iter 028 / 029, Loss: 0.395242 * Train accuracy / confusion: 81.68% / [[254, 106], [64, 504]], * Val accuracy / confusion: 74.07% / [[146, 84], [69, 291]] ------------------------------ Epoch 448 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.547088 - Iter 028 / 029, Loss: 0.442753 * Train accuracy / confusion: 82.00% / [[260, 99], [68, 501]], * Val accuracy / confusion: 75.08% / [[142, 88], [59, 301]] ------------------------------ Epoch 449 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.335604 - Iter 028 / 029, Loss: 0.359518 * Train accuracy / confusion: 81.90% / [[262, 98], [70, 498]], * Val accuracy / confusion: 73.39% / [[138, 92], [65, 295]] ------------------------------ Epoch 450 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.375072 - Iter 028 / 029, Loss: 0.583866 * Train accuracy / confusion: 81.25% / [[254, 109], [65, 500]], * Val accuracy / confusion: 73.22% / [[142, 88], [70, 290]] ------------------------------ Epoch 451 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.287089 - Iter 028 / 029, Loss: 0.521236 * Train accuracy / confusion: 82.22% / [[259, 102], [63, 504]], * Val accuracy / confusion: 73.22% / [[139, 91], [67, 293]] ------------------------------ Epoch 452 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.536013 - Iter 028 / 029, Loss: 0.383194 * Train accuracy / confusion: 82.44% / [[270, 94], [69, 495]], * Val accuracy / confusion: 74.58% / [[146, 84], [66, 294]] ------------------------------ Epoch 453 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.460353 - Iter 028 / 029, Loss: 0.251847 * Train accuracy / confusion: 81.90% / [[255, 104], [64, 505]], * Val accuracy / confusion: 73.22% / [[140, 90], [68, 292]] ------------------------------ Epoch 454 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.418830 - Iter 028 / 029, Loss: 0.433185 * Train accuracy / confusion: 81.68% / [[256, 103], [67, 502]], * Val accuracy / confusion: 72.88% / [[134, 96], [64, 296]] ------------------------------ Epoch 455 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.566999 - Iter 028 / 029, Loss: 0.549452 * Train accuracy / confusion: 82.44% / [[259, 105], [58, 506]], * Val accuracy / confusion: 75.25% / [[144, 86], [60, 300]] ------------------------------ Epoch 456 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.412785 - Iter 028 / 029, Loss: 0.329301 * Train accuracy / confusion: 82.65% / [[268, 97], [64, 499]], * Val accuracy / confusion: 71.86% / [[141, 89], [77, 283]] ------------------------------ Epoch 457 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.384275 - Iter 028 / 029, Loss: 0.451561 * Train accuracy / confusion: 81.79% / [[264, 99], [70, 495]], * Val accuracy / confusion: 74.41% / [[150, 80], [71, 289]] ------------------------------ Epoch 458 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.345960 - Iter 028 / 029, Loss: 0.584815 * Train accuracy / confusion: 81.14% / [[256, 109], [66, 497]], * Val accuracy / confusion: 73.39% / [[144, 86], [71, 289]] ------------------------------ Epoch 459 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.499513 - Iter 028 / 029, Loss: 0.422954 * Train accuracy / confusion: 80.17% / [[254, 105], [79, 490]], * Val accuracy / confusion: 73.05% / [[140, 90], [69, 291]] ------------------------------ Epoch 460 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.308054 - Iter 028 / 029, Loss: 0.549424 * Train accuracy / confusion: 82.33% / [[258, 107], [57, 506]], * Val accuracy / confusion: 75.42% / [[149, 81], [64, 296]] ------------------------------ Epoch 461 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.346429 - Iter 028 / 029, Loss: 0.510089 * Train accuracy / confusion: 81.68% / [[263, 99], [71, 495]], * Val accuracy / confusion: 73.90% / [[142, 88], [66, 294]] ------------------------------ Epoch 462 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.349402 - Iter 028 / 029, Loss: 0.390361 * Train accuracy / confusion: 80.60% / [[258, 105], [75, 490]], * Val accuracy / confusion: 74.75% / [[148, 82], [67, 293]] ------------------------------ Epoch 463 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.422630 - Iter 028 / 029, Loss: 0.537317 * Train accuracy / confusion: 81.36% / [[262, 103], [70, 493]], * Val accuracy / confusion: 75.08% / [[144, 86], [61, 299]] ------------------------------ Epoch 464 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.333863 - Iter 028 / 029, Loss: 0.406973 * Train accuracy / confusion: 81.36% / [[261, 105], [68, 494]], * Val accuracy / confusion: 73.73% / [[132, 98], [57, 303]] ------------------------------ Epoch 465 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.425729 - Iter 028 / 029, Loss: 0.511397 * Train accuracy / confusion: 80.17% / [[252, 112], [72, 492]], * Val accuracy / confusion: 72.37% / [[141, 89], [74, 286]] ------------------------------ Epoch 466 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.435593 - Iter 028 / 029, Loss: 0.391072 * Train accuracy / confusion: 81.57% / [[259, 102], [69, 498]], * Val accuracy / confusion: 74.24% / [[144, 86], [66, 294]] ------------------------------ Epoch 467 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.395049 - Iter 028 / 029, Loss: 0.388452 * Train accuracy / confusion: 81.68% / [[260, 99], [71, 498]], * Val accuracy / confusion: 73.39% / [[144, 86], [71, 289]] ------------------------------ Epoch 468 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.369386 - Iter 028 / 029, Loss: 0.490195 * Train accuracy / confusion: 80.39% / [[258, 108], [74, 488]], * Val accuracy / confusion: 73.22% / [[141, 89], [69, 291]] ------------------------------ Epoch 469 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.313237 - Iter 028 / 029, Loss: 0.482751 * Train accuracy / confusion: 81.79% / [[260, 103], [66, 499]], * Val accuracy / confusion: 73.05% / [[141, 89], [70, 290]] ------------------------------ Epoch 470 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.345183 - Iter 028 / 029, Loss: 0.521277 * Train accuracy / confusion: 80.93% / [[258, 102], [75, 493]], * Val accuracy / confusion: 71.86% / [[141, 89], [77, 283]] ------------------------------ Epoch 471 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.466116 - Iter 028 / 029, Loss: 0.498724 * Train accuracy / confusion: 82.54% / [[268, 95], [67, 498]], * Val accuracy / confusion: 75.59% / [[147, 83], [61, 299]] ------------------------------ Epoch 472 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.323219 - Iter 028 / 029, Loss: 0.386375 * Train accuracy / confusion: 81.79% / [[257, 102], [67, 502]], * Val accuracy / confusion: 73.73% / [[140, 90], [65, 295]] ------------------------------ Epoch 473 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.373600 - Iter 028 / 029, Loss: 0.352128 * Train accuracy / confusion: 80.17% / [[252, 109], [75, 492]], * Val accuracy / confusion: 74.07% / [[154, 76], [77, 283]] ------------------------------ Epoch 474 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.700005 - Iter 028 / 029, Loss: 0.517180 * Train accuracy / confusion: 80.71% / [[257, 108], [71, 492]], * Val accuracy / confusion: 73.22% / [[136, 94], [64, 296]] ------------------------------ Epoch 475 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.366180 - Iter 028 / 029, Loss: 0.390655 * Train accuracy / confusion: 81.68% / [[261, 102], [68, 497]], * Val accuracy / confusion: 74.75% / [[146, 84], [65, 295]] ------------------------------ Epoch 476 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.336024 - Iter 028 / 029, Loss: 0.419590 * Train accuracy / confusion: 79.85% / [[250, 113], [74, 491]], * Val accuracy / confusion: 73.22% / [[140, 90], [68, 292]] ------------------------------ Epoch 477 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.397156 - Iter 028 / 029, Loss: 0.434994 * Train accuracy / confusion: 81.68% / [[258, 102], [68, 500]], * Val accuracy / confusion: 73.05% / [[143, 87], [72, 288]] ------------------------------ Epoch 478 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.481219 - Iter 028 / 029, Loss: 0.530384 * Train accuracy / confusion: 81.68% / [[260, 102], [68, 498]], * Val accuracy / confusion: 73.39% / [[139, 91], [66, 294]] ------------------------------ Epoch 479 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.405363 - Iter 028 / 029, Loss: 0.441619 * Train accuracy / confusion: 81.68% / [[259, 101], [69, 499]], * Val accuracy / confusion: 74.07% / [[146, 84], [69, 291]] ------------------------------ Epoch 480 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.595391 - Iter 028 / 029, Loss: 0.438990 * Train accuracy / confusion: 82.33% / [[269, 93], [71, 495]], * Val accuracy / confusion: 71.69% / [[137, 93], [74, 286]] ------------------------------ Epoch 481 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.509994 - Iter 028 / 029, Loss: 0.484202 * Train accuracy / confusion: 81.03% / [[259, 105], [71, 493]], * Val accuracy / confusion: 74.41% / [[155, 75], [76, 284]] ------------------------------ Epoch 482 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.314125 - Iter 028 / 029, Loss: 0.421702 * Train accuracy / confusion: 82.65% / [[266, 98], [63, 501]], * Val accuracy / confusion: 73.05% / [[137, 93], [66, 294]] ------------------------------ Epoch 483 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.510541 - Iter 028 / 029, Loss: 0.459117 * Train accuracy / confusion: 81.03% / [[251, 113], [63, 501]], * Val accuracy / confusion: 72.37% / [[135, 95], [68, 292]] ------------------------------ Epoch 484 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.329436 - Iter 028 / 029, Loss: 0.284477 * Train accuracy / confusion: 80.39% / [[257, 106], [76, 489]], * Val accuracy / confusion: 74.75% / [[138, 92], [57, 303]] ------------------------------ Epoch 485 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.284713 - Iter 028 / 029, Loss: 0.396584 * Train accuracy / confusion: 82.44% / [[260, 100], [63, 505]], * Val accuracy / confusion: 71.86% / [[139, 91], [75, 285]] ------------------------------ Epoch 486 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.396515 - Iter 028 / 029, Loss: 0.339656 * Train accuracy / confusion: 80.82% / [[264, 99], [79, 486]], * Val accuracy / confusion: 72.71% / [[144, 86], [75, 285]] ------------------------------ Epoch 487 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.462090 - Iter 028 / 029, Loss: 0.410743 * Train accuracy / confusion: 81.36% / [[258, 102], [71, 497]], * Val accuracy / confusion: 72.88% / [[136, 94], [66, 294]] ------------------------------ Epoch 488 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.390172 - Iter 028 / 029, Loss: 0.432072 * Train accuracy / confusion: 81.14% / [[250, 106], [69, 503]], * Val accuracy / confusion: 75.42% / [[152, 78], [67, 293]] ------------------------------ Epoch 489 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.533423 - Iter 028 / 029, Loss: 0.347568 * Train accuracy / confusion: 81.47% / [[261, 103], [69, 495]], * Val accuracy / confusion: 71.86% / [[140, 90], [76, 284]] ------------------------------ Epoch 490 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.373709 - Iter 028 / 029, Loss: 0.352697 * Train accuracy / confusion: 81.57% / [[261, 101], [70, 496]], * Val accuracy / confusion: 74.92% / [[141, 89], [59, 301]] ------------------------------ Epoch 491 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.453348 - Iter 028 / 029, Loss: 0.510906 * Train accuracy / confusion: 81.14% / [[256, 108], [67, 497]], * Val accuracy / confusion: 73.56% / [[142, 88], [68, 292]] ------------------------------ Epoch 492 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.386341 - Iter 028 / 029, Loss: 0.270880 * Train accuracy / confusion: 81.03% / [[252, 111], [65, 500]], * Val accuracy / confusion: 73.56% / [[151, 79], [77, 283]] ------------------------------ Epoch 493 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.388330 - Iter 028 / 029, Loss: 0.471641 * Train accuracy / confusion: 80.50% / [[260, 104], [77, 487]], * Val accuracy / confusion: 72.54% / [[140, 90], [72, 288]] ------------------------------ Epoch 494 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.405912 - Iter 028 / 029, Loss: 0.350936 * Train accuracy / confusion: 80.82% / [[261, 98], [80, 489]], * Val accuracy / confusion: 73.73% / [[147, 83], [72, 288]] ------------------------------ Epoch 495 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.400960 - Iter 028 / 029, Loss: 0.515517 * Train accuracy / confusion: 79.53% / [[247, 116], [74, 491]], * Val accuracy / confusion: 72.20% / [[134, 96], [68, 292]] ------------------------------ Epoch 496 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.437835 - Iter 028 / 029, Loss: 0.395255 * Train accuracy / confusion: 80.82% / [[258, 103], [75, 492]], * Val accuracy / confusion: 72.54% / [[142, 88], [74, 286]] ------------------------------ Epoch 497 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.454821 - Iter 028 / 029, Loss: 0.263715 * Train accuracy / confusion: 82.65% / [[255, 105], [56, 512]], * Val accuracy / confusion: 75.08% / [[143, 87], [60, 300]] ------------------------------ Epoch 498 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.245078 - Iter 028 / 029, Loss: 0.565779 * Train accuracy / confusion: 81.90% / [[257, 102], [66, 503]], * Val accuracy / confusion: 72.20% / [[139, 91], [73, 287]] ------------------------------ Epoch 499 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.447749 - Iter 028 / 029, Loss: 0.604006 * Train accuracy / confusion: 81.47% / [[259, 103], [69, 497]], * Val accuracy / confusion: 74.07% / [[141, 89], [64, 296]] ------------------------------ Epoch 500 / 500, Learning rate: 1.92e-05 ------------------------------ - Iter 014 / 029, Loss: 0.507714 - Iter 028 / 029, Loss: 0.483399 * Train accuracy / confusion: 80.06% / [[258, 107], [78, 485]], * Val accuracy / confusion: 73.05% / [[140, 90], [69, 291]] **************************************** Training Ends ****************************************
- Test accuracy (last model): 73.03% - Confusion matrix (last model): [[ 897 513] [ 458 1732]]
- Test accuracy (best model): 73.03% - Confusion matrix (best model): [[ 779 631] [ 340 1850]]
# checkpoint save path
if save_checkpoint:
os.makedirs('checkpoint/', exist_ok=True)
today = datetime.date.today()
torch.save(best_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_M5_best')
torch.save(last_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_M5_last')
print('- Debug table:')
pprint.pp(last_test_debug, indent=2, width=100)
- Debug table:
{ '01183': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01303198_020317'},
'00697': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00983533_290618'},
'00825': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01129445_130220'},
'00504': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00813343_041218'},
'00192': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00608961_131118'},
'00134': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '00446328_171116'},
'00741': {'GT': 0, 'Acc': ' 20.00%', 'Pred': [6, 24], 'edfname': '01025734_280715'},
'00206': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00616193_090218'},
'01231': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01334787_211117'},
'00793': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01086373_020615'},
'01045': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '01235281_191015'},
'00407': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '00740694_110315'},
'00669': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '00957862_230317'},
'00843': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01135545_230715'},
'00029': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00164098_180919'},
'00299': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00671212_160819'},
'00702': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00985987_180518'},
'01069': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01243158_301115'},
'00913': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '01151967_160414'},
'01307': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '01376302_060718'},
'00638': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00941649_111218'},
'00286': {'GT': 1, 'Acc': ' 13.33%', 'Pred': [26, 4], 'edfname': '00663561_030414'},
'00954': {'GT': 1, 'Acc': ' 56.67%', 'Pred': [13, 17], 'edfname': '01178797_240914'},
'00587': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00894185_250817'},
'00542': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00852650_170818'},
'00996': {'GT': 1, 'Acc': ' 80.00%', 'Pred': [6, 24], 'edfname': '01204692_120315'},
'00403': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00739162_011215'},
'00408': {'GT': 0, 'Acc': ' 13.33%', 'Pred': [4, 26], 'edfname': '00740750_110315'},
'00078': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00324958_271118'},
'00277': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00657017_281218'},
'00671': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00958455_200917'},
'01066': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '01242983_071215'},
'00965': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01186214'},
'01125': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01276737_300616'},
'00227': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00626957_071217'},
'00531': {'GT': 0, 'Acc': ' 73.33%', 'Pred': [22, 8], 'edfname': '00840844_250119'},
'00088': {'GT': 1, 'Acc': ' 53.33%', 'Pred': [14, 16], 'edfname': '00344923_021116'},
'00267': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00650465_160318'},
'00069': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '00307906_230617'},
'00365': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00712852_060418'},
'00991': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01203444_090819'},
'00815': {'GT': 0, 'Acc': ' 70.00%', 'Pred': [21, 9], 'edfname': '01125477_030918'},
'01351': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01409497_111219'},
'00065': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00293228_070918'},
'00952': {'GT': 1, 'Acc': ' 53.33%', 'Pred': [14, 16], 'edfname': '01178672_300518'},
'00124': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00418981_060116'},
'00854': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01138301_230114'},
'00472': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00784418_201016'},
'01258': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01348039_181017'},
'01375': {'GT': 1, 'Acc': ' 56.67%', 'Pred': [13, 17], 'edfname': '01429374_230519'},
'00885': {'GT': 0, 'Acc': ' 30.00%', 'Pred': [9, 21], 'edfname': '01142810_180214'},
'00917': {'GT': 0, 'Acc': ' 13.33%', 'Pred': [4, 26], 'edfname': '01154159_230414'},
'00938': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '01161826_050916'},
'00881': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01141790_190214'},
'00096': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00369252_131216'},
'01075': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01250004_260116'},
'01165': {'GT': 0, 'Acc': ' 43.33%', 'Pred': [13, 17], 'edfname': '01296533_281116'},
'01067': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01242984_211215'},
'00828': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '01131959_310118'},
'01337': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01400560_160419'},
'00383': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00723110_240419'},
'00900': {'GT': 0, 'Acc': ' 3.33%', 'Pred': [1, 29], 'edfname': '01147100'},
'01336': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '01398060_050918'},
'01115': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01271298_270319'},
'00667': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00956561_241116'},
'00439': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00760780_141118'},
'00369': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '00715828_111016'},
'00955': {'GT': 1, 'Acc': ' 66.67%', 'Pred': [10, 20], 'edfname': '01178888_161117'},
'00300': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00671379_290617'},
'01196': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01307883_100217'},
'00923': {'GT': 0, 'Acc': ' 33.33%', 'Pred': [10, 20], 'edfname': '01155730_070514'},
'00058': {'GT': 0, 'Acc': ' 60.00%', 'Pred': [18, 12], 'edfname': '00285244_020414'},
'00584': {'GT': 1, 'Acc': ' 43.33%', 'Pred': [17, 13], 'edfname': '00891889_060717'},
'00749': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01027623_260916'},
'01334': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01396872_021018'},
'00588': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00895530_090616'},
'00679': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00963069_150618'},
'00385': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00723232_270318'},
'00018': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00128526_180817'},
'01281': {'GT': 1, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '01358607_280918'},
'00651': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00951808_251116'},
'01253': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01344212_240817'},
'01035': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01231654_260417'},
'00551': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '00865039_170816'},
'00870': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01139947_120214'},
'00578': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00888613_080618'},
'00730': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01011922_270815'},
'00516': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00823206_130514'},
'01330': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '01392885_240718'},
'00944': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01168853_070316'},
'00125': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '00418981_090316'},
'00508': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '00817022_010415'},
'01317': {'GT': 1, 'Acc': ' 63.33%', 'Pred': [11, 19], 'edfname': '01381606_160518'},
'00608': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '00907971_030217'},
'00471': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00784417_100315'},
'00821': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01128393_300715'},
'00122': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00416942_190516'},
'01007': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01211467_070415'},
'01247': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01339759_310717'},
'00173': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00601028_290618'},
'01026': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01225123_050815'},
'01018': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01216443_240518'},
'00418': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00745209_220916'},
'01206': {'GT': 1, 'Acc': ' 6.67%', 'Pred': [28, 2], 'edfname': '01314786_200317'},
'01215': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01321744_130417'},
'01105': {'GT': 0, 'Acc': ' 30.00%', 'Pred': [9, 21], 'edfname': '01266696_110516'},
'00598': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00899964_110414'},
'00851': {'GT': 0, 'Acc': ' 73.33%', 'Pred': [22, 8], 'edfname': '01138297_230114'},
'01138': {'GT': 0, 'Acc': ' 60.00%', 'Pred': [18, 12], 'edfname': '01281605_070716'},
'00079': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00325929_170119'},
'00245': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00637371_050917'},
'00591': {'GT': 0, 'Acc': ' 73.33%', 'Pred': [22, 8], 'edfname': '00896386_240914'},
'00329': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '00685248_150414'},
'00272': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00651389_281016'},
'00176': {'GT': 0, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '00602435_270217'},
'00807': {'GT': 1, 'Acc': ' 13.33%', 'Pred': [26, 4], 'edfname': '01112291_231115'},
'00271': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00651252_140618'},
'00712': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00988278_210915'},
'00974': {'GT': 1, 'Acc': ' 43.33%', 'Pred': [17, 13], 'edfname': '01193508_171214'},
'01163': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01296342_141116'}}
class BasicResBlock(nn.Module):
expansion: int = 1
def __init__(self, c_in, c_out, kernel_size, stride) -> None:
super().__init__()
self.conv1 = nn.Conv1d(in_channels=c_in, out_channels=c_out,
kernel_size=kernel_size, stride=stride,
padding=kernel_size//2, bias=False)
self.bn1 = nn.BatchNorm1d(c_out)
self.conv2 = nn.Conv1d(in_channels=c_out, out_channels=c_out,
kernel_size=kernel_size, stride=1,
padding=kernel_size//2, bias=False)
self.bn2 = nn.BatchNorm1d(c_out)
self.relu = nn.ReLU(inplace=True)
self.downsample = None
if stride != 1 or c_in != c_out:
self.downsample = nn.Sequential(
nn.Conv1d(in_channels=c_in, out_channels=c_out,
kernel_size=1, stride=stride, bias=False),
nn.BatchNorm1d(c_out)
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
identity = x
x = self.conv1(x)
x = self.bn1(x)
x = self.relu(x)
x = self.conv2(x)
x = self.bn2(x)
if self.downsample is not None:
identity = self.downsample(identity)
x = self.relu(x + identity)
return x
class BottleneckBlock(nn.Module):
expansion: int = 4
def __init__(self, c_in, c_out, kernel_size, stride) -> None:
super().__init__()
width = c_out
self.conv1 = nn.Conv1d(in_channels=c_in, out_channels=width,
kernel_size=1, stride=1, bias=False)
self.bn1 = nn.BatchNorm1d(width)
self.conv2 = nn.Conv1d(in_channels=width, out_channels=width,
kernel_size=kernel_size, stride=stride,
padding=kernel_size//2, bias=False)
self.bn2 = nn.BatchNorm1d(width)
self.conv3 = nn.Conv1d(in_channels=width, out_channels=c_out*self.expansion,
kernel_size=1, stride=1, bias=False)
self.bn3 = nn.BatchNorm1d(c_out*self.expansion)
self.relu = nn.ReLU(inplace=True)
self.downsample = None
if stride != 1 or c_in != c_out*self.expansion:
self.downsample = nn.Sequential(
nn.Conv1d(in_channels=c_in, out_channels=c_out*self.expansion,
kernel_size=1, stride=stride, bias=False),
nn.BatchNorm1d(c_out*self.expansion)
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
identity = x
x = self.conv1(x)
x = self.bn1(x)
x = self.relu(x)
x = self.conv2(x)
x = self.bn2(x)
x = self.relu(x)
x = self.conv3(x)
x = self.bn3(x)
if self.downsample is not None:
identity = self.downsample(identity)
x = self.relu(x + identity)
return x
class ResNet(nn.Module):
def __init__(self,
block: Type[Union[BasicResBlock, BottleneckBlock]],
conv_layers: List[int],
n_fc: int,
n_input=20,
n_output=3,
n_start=64,
kernel_size=9,
use_age=True,
final_pool='average') -> None:
super().__init__()
if final_pool not in {'average', 'max'}:
raise ValueError("final_pool must be set to one of ['average', 'max']")
self.c_current = n_start
self.use_age = use_age
self.input_stage = nn.Sequential(
nn.Conv1d(in_channels=n_input, out_channels=n_start,
kernel_size=kernel_size*3, stride=2,
padding=(kernel_size*3)//2, bias=False),
nn.BatchNorm1d(n_start),
nn.ReLU(),
)
self.conv_stage1 = self._make_conv_layer(block, conv_layers[0], n_start, kernel_size, stride=3)
self.conv_stage2 = self._make_conv_layer(block, conv_layers[1], n_start*2, kernel_size, stride=3)
self.conv_stage3 = self._make_conv_layer(block, conv_layers[2], n_start*4, kernel_size, stride=3)
self.conv_stage4 = self._make_conv_layer(block, conv_layers[3], n_start*8, kernel_size, stride=3)
if final_pool == 'average':
self.final_pool = nn.AdaptiveAvgPool1d(1)
elif final_pool == 'max':
self.final_pool = nn.AdaptiveMaxPool1d(1)
fc_layers = []
if self.use_age:
self.c_current = self.c_current + 1
for l in range(n_fc):
layer = nn.Sequential(nn.Linear(self.c_current, self.c_current // 2, bias=False),
nn.Dropout(p=0.1),
nn.BatchNorm1d(self.c_current // 2),
nn.ReLU())
self.c_current = self.c_current // 2
fc_layers.append(layer)
fc_layers.append(nn.Linear(self.c_current, n_output))
self.fc_stage = nn.Sequential(*fc_layers)
def reset_weights(self):
for m in self.modules():
if hasattr(m, 'reset_parameters'):
m.reset_parameters()
def _make_conv_layer(self, block: Type[Union[BasicResBlock, BottleneckBlock]],
n_block: int, c_out: int, kernel_size: int, stride: int = 1) -> nn.Sequential:
layers = []
c_in = self.c_current
layers.append(block(c_in, c_out, kernel_size, stride=1))
c_in = c_out * block.expansion
self.c_current = c_in
for _ in range(1, n_block):
layers.append(block(c_in, c_out, kernel_size, stride=1))
layers.append(nn.MaxPool1d(kernel_size=stride))
return nn.Sequential(*layers)
def forward(self, x, age, print_shape=False):
x = self.input_stage(x)
x = self.conv_stage1(x)
x = self.conv_stage2(x)
x = self.conv_stage3(x)
x = self.conv_stage4(x)
if print_shape:
print('Shape right before squeezing:', x.shape)
x = self.final_pool(x).squeeze()
if self.use_age:
x = torch.cat((x, age.reshape(-1, 1)), dim=1)
x = self.fc_stage(x)
return x
# return F.log_softmax(x, dim=2)
model = ResNet(block=BottleneckBlock,
conv_layers=[2, 2, 2, 2],
n_fc=3,
n_input=train_dataset[0]['signal'].shape[0],
n_output=2,
n_start=64,
kernel_size=9,
use_age=True,
final_pool='max')
model = model.to(device, dtype=torch.float32)
print(model)
print()
# tensorboard visualization
visualize_network_tensorboard(model, 'ResNet-like')
# number of parameters
n = count_parameters(model)
print(f'The Number of parameters of the model: {n:,}')
ResNet(
(input_stage): Sequential(
(0): Conv1d(20, 64, kernel_size=(27,), stride=(2,), padding=(13,), bias=False)
(1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(2): ReLU()
)
(conv_stage1): Sequential(
(0): BottleneckBlock(
(conv1): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(64, 64, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(64, 256, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(64, 256, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): BottleneckBlock(
(conv1): Conv1d(256, 64, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(64, 64, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(64, 256, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(2): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(conv_stage2): Sequential(
(0): BottleneckBlock(
(conv1): Conv1d(256, 128, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(128, 128, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(128, 512, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(256, 512, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): BottleneckBlock(
(conv1): Conv1d(512, 128, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(128, 128, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(128, 512, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(2): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(conv_stage3): Sequential(
(0): BottleneckBlock(
(conv1): Conv1d(512, 256, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(256, 256, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(256, 1024, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(512, 1024, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): BottleneckBlock(
(conv1): Conv1d(1024, 256, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(256, 256, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(256, 1024, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(2): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(conv_stage4): Sequential(
(0): BottleneckBlock(
(conv1): Conv1d(1024, 512, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(512, 512, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(512, 2048, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(1024, 2048, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): BottleneckBlock(
(conv1): Conv1d(2048, 512, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(512, 512, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(512, 2048, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(2): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(final_pool): AdaptiveMaxPool1d(output_size=1)
(fc_stage): Sequential(
(0): Sequential(
(0): Linear(in_features=2049, out_features=1024, bias=False)
(1): Dropout(p=0.1, inplace=False)
(2): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU()
)
(1): Sequential(
(0): Linear(in_features=1024, out_features=512, bias=False)
(1): Dropout(p=0.1, inplace=False)
(2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU()
)
(2): Sequential(
(0): Linear(in_features=512, out_features=256, bias=False)
(1): Dropout(p=0.1, inplace=False)
(2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU()
)
(3): Linear(in_features=256, out_features=2, bias=True)
)
)
Shape right before squeezing: torch.Size([32, 2048, 12])
The Number of parameters of the model: 16,728,962
record = learning_rate_search(model,
min_log_lr=-4.5,
max_log_lr=-1.4,
trials=300,
epochs=1)
draw_learning_rate_record(record)
best_log_lr = record[np.argmax(np.array([v for lr, v in record]))][0]
# best_log_lr = -3.5
print('best_log_lr:', best_log_lr)
best_log_lr: -2.561406555942617
# reduce the learning after [lr_schedule_step] epochs by a factor of 10
n_epoch = 500
lr_schedule_step = 200
log_interval = len(train_loader) // 2
loss_history = []
train_acc_history = []
val_acc_history = []
best_val_acc = 0
model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=10 ** best_log_lr, weight_decay=0.0001)
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=lr_schedule_step, gamma=0.1)
print(f'{"*"*40} Training Starts {"*"*40}')
for epoch in tqdm(range(1, n_epoch + 1)):
print(f'{"-"*30} Epoch {epoch:03d} / {n_epoch:03d}, Learning rate: {optimizer.param_groups[-1]["lr"]:.2e} {"-"*30}')
# train
loss, train_accuracy, train_confusion = train_one_epoch(model, optimizer, log_interval)
loss_history.extend(loss)
train_acc_history.append(train_accuracy)
# validation
val_accuracy, val_confusion = check_val_accuracy(model, repeat=5)
val_acc_history.append(val_accuracy)
if best_val_acc < val_accuracy:
best_val_acc = val_accuracy
best_model_state = deepcopy(model.state_dict())
# learning rate schedule
scheduler.step()
print()
print(f'* Train accuracy / confusion: {train_accuracy:.2f}% / {train_confusion.tolist()}, ')
print(f'* Val accuracy / confusion: {val_accuracy:.2f}% / {val_confusion.tolist()}')
print()
print(f'{"*"*40} Training Ends {"*"*40}')
# draw the training loss plot
draw_loss_plot(loss_history)
draw_accuracy_history(train_acc_history, val_acc_history)
# test the last model
last_model_state = deepcopy(model.state_dict())
last_test_accuracy, last_test_confusion, last_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (last model): {last_test_accuracy:.2f}%')
print('- Confusion matrix (last model):\n', last_test_confusion)
print()
draw_confusion(last_test_confusion)
# test the best model
model.load_state_dict(best_model_state)
best_test_accuracy, best_test_confusion, best_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (best model): {best_test_accuracy:.2f}%')
print('- Confusion matrix (best model):\n', best_test_confusion)
print()
draw_confusion(best_test_confusion)
**************************************** Training Starts ****************************************
------------------------------ Epoch 001 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.644670 - Iter 028 / 029, Loss: 0.745010 * Train accuracy / confusion: 59.27% / [[57, 305], [73, 493]], * Val accuracy / confusion: 57.80% / [[82, 148], [101, 259]] ------------------------------ Epoch 002 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.638908 - Iter 028 / 029, Loss: 0.649859 * Train accuracy / confusion: 60.24% / [[9, 354], [15, 550]], * Val accuracy / confusion: 60.17% / [[15, 215], [20, 340]] ------------------------------ Epoch 003 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.672112 - Iter 028 / 029, Loss: 0.867415 * Train accuracy / confusion: 60.24% / [[14, 349], [20, 545]], * Val accuracy / confusion: 57.12% / [[18, 212], [41, 319]] ------------------------------ Epoch 004 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.774632 - Iter 028 / 029, Loss: 0.723529 * Train accuracy / confusion: 59.05% / [[41, 324], [56, 507]], * Val accuracy / confusion: 46.27% / [[177, 53], [264, 96]] ------------------------------ Epoch 005 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.680691 - Iter 028 / 029, Loss: 0.692041 * Train accuracy / confusion: 60.13% / [[12, 350], [20, 546]], * Val accuracy / confusion: 58.14% / [[54, 176], [71, 289]] ------------------------------ Epoch 006 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.616167 - Iter 028 / 029, Loss: 0.679129 * Train accuracy / confusion: 58.51% / [[28, 334], [51, 515]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 007 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.636549 - Iter 028 / 029, Loss: 0.612225 * Train accuracy / confusion: 60.88% / [[45, 316], [47, 520]], * Val accuracy / confusion: 58.64% / [[31, 199], [45, 315]] ------------------------------ Epoch 008 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.667415 - Iter 028 / 029, Loss: 0.634167 * Train accuracy / confusion: 59.05% / [[15, 349], [31, 533]], * Val accuracy / confusion: 58.81% / [[44, 186], [57, 303]] ------------------------------ Epoch 009 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.648577 - Iter 028 / 029, Loss: 0.637284 * Train accuracy / confusion: 59.59% / [[15, 349], [26, 538]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 010 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.682927 - Iter 028 / 029, Loss: 0.707139 * Train accuracy / confusion: 59.81% / [[10, 355], [18, 545]], * Val accuracy / confusion: 59.49% / [[14, 216], [23, 337]] ------------------------------ Epoch 011 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.658257 - Iter 028 / 029, Loss: 0.760335 * Train accuracy / confusion: 60.24% / [[10, 352], [17, 549]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 012 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.675185 - Iter 028 / 029, Loss: 0.677406 * Train accuracy / confusion: 60.56% / [[4, 355], [11, 558]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 013 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.663284 - Iter 028 / 029, Loss: 0.727438 * Train accuracy / confusion: 60.67% / [[10, 350], [15, 553]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 014 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.703057 - Iter 028 / 029, Loss: 0.655900 * Train accuracy / confusion: 60.99% / [[23, 339], [23, 543]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 015 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.680526 - Iter 028 / 029, Loss: 0.702060 * Train accuracy / confusion: 60.45% / [[32, 335], [32, 529]], * Val accuracy / confusion: 59.49% / [[20, 210], [29, 331]] ------------------------------ Epoch 016 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.732440 - Iter 028 / 029, Loss: 0.695343 * Train accuracy / confusion: 60.24% / [[19, 343], [26, 540]], * Val accuracy / confusion: 61.02% / [[6, 224], [6, 354]] ------------------------------ Epoch 017 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.771961 - Iter 028 / 029, Loss: 0.789541 * Train accuracy / confusion: 59.59% / [[12, 352], [23, 541]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 018 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.652855 - Iter 028 / 029, Loss: 0.718768 * Train accuracy / confusion: 60.02% / [[25, 334], [37, 532]], * Val accuracy / confusion: 55.76% / [[25, 205], [56, 304]] ------------------------------ Epoch 019 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.657364 - Iter 028 / 029, Loss: 0.717036 * Train accuracy / confusion: 61.64% / [[13, 348], [8, 559]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 020 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.637488 - Iter 028 / 029, Loss: 0.624419 * Train accuracy / confusion: 60.56% / [[12, 350], [16, 550]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 021 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.626449 - Iter 028 / 029, Loss: 0.629064 * Train accuracy / confusion: 61.21% / [[5, 354], [6, 563]], * Val accuracy / confusion: 58.47% / [[9, 221], [24, 336]] ------------------------------ Epoch 022 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.700085 - Iter 028 / 029, Loss: 0.674854 * Train accuracy / confusion: 60.02% / [[11, 352], [19, 546]], * Val accuracy / confusion: 59.66% / [[22, 208], [30, 330]] ------------------------------ Epoch 023 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.690385 - Iter 028 / 029, Loss: 0.634087 * Train accuracy / confusion: 60.02% / [[39, 325], [46, 518]], * Val accuracy / confusion: 60.00% / [[21, 209], [27, 333]] ------------------------------ Epoch 024 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.664304 - Iter 028 / 029, Loss: 0.678125 * Train accuracy / confusion: 60.24% / [[9, 353], [16, 550]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 025 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.694866 - Iter 028 / 029, Loss: 0.644154 * Train accuracy / confusion: 60.56% / [[6, 355], [11, 556]], * Val accuracy / confusion: 57.97% / [[13, 217], [31, 329]] ------------------------------ Epoch 026 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.814333 - Iter 028 / 029, Loss: 0.616311 * Train accuracy / confusion: 60.99% / [[13, 346], [16, 553]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 027 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.723666 - Iter 028 / 029, Loss: 0.629668 * Train accuracy / confusion: 60.02% / [[19, 347], [24, 538]], * Val accuracy / confusion: 61.53% / [[4, 226], [1, 359]] ------------------------------ Epoch 028 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.650317 - Iter 028 / 029, Loss: 0.702771 * Train accuracy / confusion: 60.13% / [[3, 356], [14, 555]], * Val accuracy / confusion: 61.19% / [[1, 229], [0, 360]] ------------------------------ Epoch 029 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.609975 - Iter 028 / 029, Loss: 0.682831 * Train accuracy / confusion: 60.45% / [[10, 352], [15, 551]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 030 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.673318 - Iter 028 / 029, Loss: 0.698171 * Train accuracy / confusion: 60.34% / [[10, 353], [15, 550]], * Val accuracy / confusion: 60.51% / [[20, 210], [23, 337]] ------------------------------ Epoch 031 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.718451 - Iter 028 / 029, Loss: 0.721166 * Train accuracy / confusion: 59.38% / [[32, 332], [45, 519]], * Val accuracy / confusion: 56.61% / [[9, 221], [35, 325]] ------------------------------ Epoch 032 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.785854 - Iter 028 / 029, Loss: 0.669974 * Train accuracy / confusion: 60.88% / [[1, 359], [4, 564]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 033 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.598002 - Iter 028 / 029, Loss: 0.697453 * Train accuracy / confusion: 60.34% / [[14, 349], [19, 546]], * Val accuracy / confusion: 58.31% / [[34, 196], [50, 310]] ------------------------------ Epoch 034 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.647858 - Iter 028 / 029, Loss: 0.811316 * Train accuracy / confusion: 59.70% / [[17, 345], [29, 537]], * Val accuracy / confusion: 61.53% / [[63, 167], [60, 300]] ------------------------------ Epoch 035 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.733414 - Iter 028 / 029, Loss: 0.652821 * Train accuracy / confusion: 60.02% / [[11, 353], [18, 546]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 036 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.678377 - Iter 028 / 029, Loss: 0.704869 * Train accuracy / confusion: 60.45% / [[16, 348], [19, 545]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 037 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.630756 - Iter 028 / 029, Loss: 0.728877 * Train accuracy / confusion: 61.10% / [[9, 357], [4, 558]], * Val accuracy / confusion: 59.49% / [[50, 180], [59, 301]] ------------------------------ Epoch 038 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.797622 - Iter 028 / 029, Loss: 0.717088 * Train accuracy / confusion: 61.31% / [[48, 311], [48, 521]], * Val accuracy / confusion: 61.36% / [[3, 227], [1, 359]] ------------------------------ Epoch 039 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.676870 - Iter 028 / 029, Loss: 0.718525 * Train accuracy / confusion: 61.53% / [[12, 351], [6, 559]], * Val accuracy / confusion: 61.02% / [[0, 230], [0, 360]] ------------------------------ Epoch 040 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.658629 - Iter 028 / 029, Loss: 0.706446 * Train accuracy / confusion: 65.41% / [[105, 257], [64, 502]], * Val accuracy / confusion: 61.02% / [[3, 227], [3, 357]] ------------------------------ Epoch 041 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.516066 - Iter 028 / 029, Loss: 0.611194 * Train accuracy / confusion: 67.56% / [[178, 184], [117, 449]], * Val accuracy / confusion: 67.97% / [[47, 183], [6, 354]] ------------------------------ Epoch 042 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.503231 - Iter 028 / 029, Loss: 0.570772 * Train accuracy / confusion: 68.00% / [[143, 219], [78, 488]], * Val accuracy / confusion: 64.07% / [[19, 211], [1, 359]] ------------------------------ Epoch 043 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.592222 - Iter 028 / 029, Loss: 0.555303 * Train accuracy / confusion: 71.88% / [[207, 150], [111, 460]], * Val accuracy / confusion: 60.51% / [[10, 220], [13, 347]] ------------------------------ Epoch 044 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.524938 - Iter 028 / 029, Loss: 0.704303 * Train accuracy / confusion: 70.15% / [[165, 193], [84, 486]], * Val accuracy / confusion: 71.69% / [[91, 139], [28, 332]] ------------------------------ Epoch 045 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.421414 - Iter 028 / 029, Loss: 0.698905 * Train accuracy / confusion: 69.94% / [[160, 202], [77, 489]], * Val accuracy / confusion: 39.83% / [[211, 19], [336, 24]] ------------------------------ Epoch 046 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.607128 - Iter 028 / 029, Loss: 0.613303 * Train accuracy / confusion: 67.89% / [[174, 187], [111, 456]], * Val accuracy / confusion: 59.83% / [[186, 44], [193, 167]] ------------------------------ Epoch 047 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.587314 - Iter 028 / 029, Loss: 0.563967 * Train accuracy / confusion: 63.90% / [[117, 247], [88, 476]], * Val accuracy / confusion: 59.66% / [[197, 33], [205, 155]] ------------------------------ Epoch 048 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.554210 - Iter 028 / 029, Loss: 0.589354 * Train accuracy / confusion: 68.00% / [[164, 197], [100, 467]], * Val accuracy / confusion: 65.59% / [[160, 70], [133, 227]] ------------------------------ Epoch 049 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.492169 - Iter 028 / 029, Loss: 0.581100 * Train accuracy / confusion: 69.72% / [[183, 177], [104, 464]], * Val accuracy / confusion: 68.64% / [[108, 122], [63, 297]] ------------------------------ Epoch 050 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.684753 - Iter 028 / 029, Loss: 0.790375 * Train accuracy / confusion: 69.83% / [[178, 185], [95, 470]], * Val accuracy / confusion: 66.10% / [[32, 198], [2, 358]] ------------------------------ Epoch 051 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.659775 - Iter 028 / 029, Loss: 0.532649 * Train accuracy / confusion: 69.40% / [[185, 180], [104, 459]], * Val accuracy / confusion: 75.59% / [[141, 89], [55, 305]] ------------------------------ Epoch 052 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.512051 - Iter 028 / 029, Loss: 0.638380 * Train accuracy / confusion: 71.66% / [[182, 179], [84, 483]], * Val accuracy / confusion: 75.42% / [[118, 112], [33, 327]] ------------------------------ Epoch 053 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.477207 - Iter 028 / 029, Loss: 0.549748 * Train accuracy / confusion: 70.15% / [[188, 176], [101, 463]], * Val accuracy / confusion: 71.02% / [[67, 163], [8, 352]] ------------------------------ Epoch 054 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.799358 - Iter 028 / 029, Loss: 0.388486 * Train accuracy / confusion: 70.69% / [[197, 163], [109, 459]], * Val accuracy / confusion: 75.08% / [[114, 116], [31, 329]] ------------------------------ Epoch 055 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.431293 - Iter 028 / 029, Loss: 0.717996 * Train accuracy / confusion: 69.83% / [[197, 167], [113, 451]], * Val accuracy / confusion: 70.68% / [[129, 101], [72, 288]] ------------------------------ Epoch 056 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.439072 - Iter 028 / 029, Loss: 0.597329 * Train accuracy / confusion: 71.77% / [[198, 167], [95, 468]], * Val accuracy / confusion: 74.92% / [[129, 101], [47, 313]] ------------------------------ Epoch 057 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.564264 - Iter 028 / 029, Loss: 0.597876 * Train accuracy / confusion: 70.80% / [[208, 155], [116, 449]], * Val accuracy / confusion: 72.88% / [[132, 98], [62, 298]] ------------------------------ Epoch 058 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.542687 - Iter 028 / 029, Loss: 0.418623 * Train accuracy / confusion: 72.52% / [[193, 167], [88, 480]], * Val accuracy / confusion: 74.24% / [[103, 127], [25, 335]] ------------------------------ Epoch 059 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.563500 - Iter 028 / 029, Loss: 0.512664 * Train accuracy / confusion: 69.18% / [[183, 181], [105, 459]], * Val accuracy / confusion: 73.90% / [[138, 92], [62, 298]] ------------------------------ Epoch 060 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.437535 - Iter 028 / 029, Loss: 0.475196 * Train accuracy / confusion: 74.03% / [[214, 149], [92, 473]], * Val accuracy / confusion: 74.07% / [[130, 100], [53, 307]] ------------------------------ Epoch 061 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.528091 - Iter 028 / 029, Loss: 0.534164 * Train accuracy / confusion: 73.06% / [[216, 146], [104, 462]], * Val accuracy / confusion: 75.25% / [[146, 84], [62, 298]] ------------------------------ Epoch 062 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.444561 - Iter 028 / 029, Loss: 0.572196 * Train accuracy / confusion: 72.84% / [[217, 146], [106, 459]], * Val accuracy / confusion: 70.68% / [[171, 59], [114, 246]] ------------------------------ Epoch 063 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.496806 - Iter 028 / 029, Loss: 0.748794 * Train accuracy / confusion: 73.06% / [[227, 135], [115, 451]], * Val accuracy / confusion: 74.75% / [[108, 122], [27, 333]] ------------------------------ Epoch 064 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.574221 - Iter 028 / 029, Loss: 0.550376 * Train accuracy / confusion: 73.92% / [[223, 137], [105, 463]], * Val accuracy / confusion: 75.76% / [[128, 102], [41, 319]] ------------------------------ Epoch 065 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.524427 - Iter 028 / 029, Loss: 0.512906 * Train accuracy / confusion: 72.31% / [[206, 153], [104, 465]], * Val accuracy / confusion: 74.24% / [[112, 118], [34, 326]] ------------------------------ Epoch 066 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.635360 - Iter 028 / 029, Loss: 0.497736 * Train accuracy / confusion: 72.41% / [[189, 171], [85, 483]], * Val accuracy / confusion: 72.54% / [[147, 83], [79, 281]] ------------------------------ Epoch 067 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.534143 - Iter 028 / 029, Loss: 0.451379 * Train accuracy / confusion: 73.38% / [[219, 144], [103, 462]], * Val accuracy / confusion: 77.63% / [[130, 100], [32, 328]] ------------------------------ Epoch 068 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.395060 - Iter 028 / 029, Loss: 0.797427 * Train accuracy / confusion: 73.60% / [[216, 146], [99, 467]], * Val accuracy / confusion: 75.08% / [[125, 105], [42, 318]] ------------------------------ Epoch 069 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.517716 - Iter 028 / 029, Loss: 0.623880 * Train accuracy / confusion: 72.95% / [[209, 153], [98, 468]], * Val accuracy / confusion: 74.07% / [[101, 129], [24, 336]] ------------------------------ Epoch 070 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.450777 - Iter 028 / 029, Loss: 0.591589 * Train accuracy / confusion: 73.60% / [[214, 151], [94, 469]], * Val accuracy / confusion: 74.58% / [[125, 105], [45, 315]] ------------------------------ Epoch 071 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.488220 - Iter 028 / 029, Loss: 0.587824 * Train accuracy / confusion: 74.14% / [[217, 145], [95, 471]], * Val accuracy / confusion: 72.71% / [[129, 101], [60, 300]] ------------------------------ Epoch 072 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.560366 - Iter 028 / 029, Loss: 0.404665 * Train accuracy / confusion: 75.00% / [[217, 145], [87, 479]], * Val accuracy / confusion: 72.54% / [[102, 128], [34, 326]] ------------------------------ Epoch 073 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.662213 - Iter 028 / 029, Loss: 0.674119 * Train accuracy / confusion: 72.95% / [[203, 158], [93, 474]], * Val accuracy / confusion: 76.44% / [[116, 114], [25, 335]] ------------------------------ Epoch 074 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.571250 - Iter 028 / 029, Loss: 0.641377 * Train accuracy / confusion: 72.20% / [[199, 164], [94, 471]], * Val accuracy / confusion: 75.76% / [[112, 118], [25, 335]] ------------------------------ Epoch 075 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.395425 - Iter 028 / 029, Loss: 0.478034 * Train accuracy / confusion: 73.06% / [[211, 153], [97, 467]], * Val accuracy / confusion: 75.93% / [[137, 93], [49, 311]] ------------------------------ Epoch 076 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.660930 - Iter 028 / 029, Loss: 0.677270 * Train accuracy / confusion: 72.84% / [[205, 158], [94, 471]], * Val accuracy / confusion: 76.27% / [[136, 94], [46, 314]] ------------------------------ Epoch 077 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.646968 - Iter 028 / 029, Loss: 0.631745 * Train accuracy / confusion: 71.55% / [[188, 170], [94, 476]], * Val accuracy / confusion: 69.66% / [[79, 151], [28, 332]] ------------------------------ Epoch 078 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.447319 - Iter 028 / 029, Loss: 0.650552 * Train accuracy / confusion: 72.20% / [[210, 151], [107, 460]], * Val accuracy / confusion: 74.92% / [[142, 88], [60, 300]] ------------------------------ Epoch 079 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.705333 - Iter 028 / 029, Loss: 0.531653 * Train accuracy / confusion: 73.92% / [[210, 151], [91, 476]], * Val accuracy / confusion: 76.10% / [[113, 117], [24, 336]] ------------------------------ Epoch 080 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.497228 - Iter 028 / 029, Loss: 0.389785 * Train accuracy / confusion: 73.60% / [[206, 152], [93, 477]], * Val accuracy / confusion: 72.37% / [[158, 72], [91, 269]] ------------------------------ Epoch 081 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.541968 - Iter 028 / 029, Loss: 0.505501 * Train accuracy / confusion: 74.57% / [[218, 146], [90, 474]], * Val accuracy / confusion: 75.25% / [[126, 104], [42, 318]] ------------------------------ Epoch 082 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.493508 - Iter 028 / 029, Loss: 0.415831 * Train accuracy / confusion: 72.41% / [[211, 153], [103, 461]], * Val accuracy / confusion: 67.80% / [[58, 172], [18, 342]] ------------------------------ Epoch 083 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.462394 - Iter 028 / 029, Loss: 0.599287 * Train accuracy / confusion: 74.03% / [[225, 142], [99, 462]], * Val accuracy / confusion: 72.20% / [[151, 79], [85, 275]] ------------------------------ Epoch 084 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.644322 - Iter 028 / 029, Loss: 0.787935 * Train accuracy / confusion: 73.92% / [[207, 158], [84, 479]], * Val accuracy / confusion: 73.73% / [[113, 117], [38, 322]] ------------------------------ Epoch 085 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.541229 - Iter 028 / 029, Loss: 0.489958 * Train accuracy / confusion: 73.49% / [[222, 143], [103, 460]], * Val accuracy / confusion: 75.42% / [[136, 94], [51, 309]] ------------------------------ Epoch 086 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.529641 - Iter 028 / 029, Loss: 0.628777 * Train accuracy / confusion: 74.89% / [[218, 145], [88, 477]], * Val accuracy / confusion: 75.59% / [[123, 107], [37, 323]] ------------------------------ Epoch 087 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.521479 - Iter 028 / 029, Loss: 0.528171 * Train accuracy / confusion: 76.51% / [[221, 138], [80, 489]], * Val accuracy / confusion: 72.88% / [[159, 71], [89, 271]] ------------------------------ Epoch 088 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.592988 - Iter 028 / 029, Loss: 0.636709 * Train accuracy / confusion: 75.54% / [[237, 127], [100, 464]], * Val accuracy / confusion: 74.07% / [[124, 106], [47, 313]] ------------------------------ Epoch 089 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.584388 - Iter 028 / 029, Loss: 0.657834 * Train accuracy / confusion: 74.78% / [[211, 146], [88, 483]], * Val accuracy / confusion: 74.75% / [[117, 113], [36, 324]] ------------------------------ Epoch 090 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.448074 - Iter 028 / 029, Loss: 0.616627 * Train accuracy / confusion: 74.89% / [[232, 133], [100, 463]], * Val accuracy / confusion: 69.83% / [[68, 162], [16, 344]] ------------------------------ Epoch 091 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.473617 - Iter 028 / 029, Loss: 0.705308 * Train accuracy / confusion: 74.03% / [[213, 151], [90, 474]], * Val accuracy / confusion: 74.75% / [[129, 101], [48, 312]] ------------------------------ Epoch 092 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.702561 - Iter 028 / 029, Loss: 0.514702 * Train accuracy / confusion: 75.75% / [[230, 133], [92, 473]], * Val accuracy / confusion: 75.76% / [[160, 70], [73, 287]] ------------------------------ Epoch 093 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.452088 - Iter 028 / 029, Loss: 0.663112 * Train accuracy / confusion: 76.72% / [[232, 126], [90, 480]], * Val accuracy / confusion: 72.71% / [[144, 86], [75, 285]] ------------------------------ Epoch 094 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.397798 - Iter 028 / 029, Loss: 0.598966 * Train accuracy / confusion: 75.43% / [[229, 131], [97, 471]], * Val accuracy / confusion: 74.41% / [[124, 106], [45, 315]] ------------------------------ Epoch 095 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.528986 - Iter 028 / 029, Loss: 0.426576 * Train accuracy / confusion: 73.81% / [[213, 150], [93, 472]], * Val accuracy / confusion: 76.78% / [[141, 89], [48, 312]] ------------------------------ Epoch 096 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.419228 - Iter 028 / 029, Loss: 0.703874 * Train accuracy / confusion: 74.35% / [[220, 139], [99, 470]], * Val accuracy / confusion: 75.76% / [[136, 94], [49, 311]] ------------------------------ Epoch 097 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.581888 - Iter 028 / 029, Loss: 0.648057 * Train accuracy / confusion: 73.28% / [[221, 145], [103, 459]], * Val accuracy / confusion: 72.37% / [[170, 60], [103, 257]] ------------------------------ Epoch 098 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.347615 - Iter 028 / 029, Loss: 0.508826 * Train accuracy / confusion: 74.46% / [[225, 136], [101, 466]], * Val accuracy / confusion: 75.25% / [[132, 98], [48, 312]] ------------------------------ Epoch 099 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.453874 - Iter 028 / 029, Loss: 0.447897 * Train accuracy / confusion: 74.89% / [[224, 143], [90, 471]], * Val accuracy / confusion: 73.73% / [[108, 122], [33, 327]] ------------------------------ Epoch 100 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.673402 - Iter 028 / 029, Loss: 0.428906 * Train accuracy / confusion: 75.97% / [[240, 125], [98, 465]], * Val accuracy / confusion: 72.20% / [[141, 89], [75, 285]] ------------------------------ Epoch 101 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.417550 - Iter 028 / 029, Loss: 0.629892 * Train accuracy / confusion: 75.22% / [[229, 132], [98, 469]], * Val accuracy / confusion: 73.22% / [[134, 96], [62, 298]] ------------------------------ Epoch 102 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.406241 - Iter 028 / 029, Loss: 0.387004 * Train accuracy / confusion: 75.00% / [[233, 131], [101, 463]], * Val accuracy / confusion: 72.71% / [[153, 77], [84, 276]] ------------------------------ Epoch 103 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.584851 - Iter 028 / 029, Loss: 0.613348 * Train accuracy / confusion: 76.40% / [[221, 138], [81, 488]], * Val accuracy / confusion: 71.86% / [[166, 64], [102, 258]] ------------------------------ Epoch 104 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.591137 - Iter 028 / 029, Loss: 0.548778 * Train accuracy / confusion: 74.03% / [[219, 142], [99, 468]], * Val accuracy / confusion: 75.25% / [[134, 96], [50, 310]] ------------------------------ Epoch 105 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.498538 - Iter 028 / 029, Loss: 0.399746 * Train accuracy / confusion: 73.92% / [[239, 122], [120, 447]], * Val accuracy / confusion: 73.73% / [[151, 79], [76, 284]] ------------------------------ Epoch 106 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.576672 - Iter 028 / 029, Loss: 0.640240 * Train accuracy / confusion: 74.78% / [[220, 142], [92, 474]], * Val accuracy / confusion: 75.25% / [[153, 77], [69, 291]] ------------------------------ Epoch 107 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.367399 - Iter 028 / 029, Loss: 0.459972 * Train accuracy / confusion: 76.62% / [[235, 128], [89, 476]], * Val accuracy / confusion: 67.46% / [[94, 136], [56, 304]] ------------------------------ Epoch 108 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.643075 - Iter 028 / 029, Loss: 0.498396 * Train accuracy / confusion: 74.25% / [[212, 149], [90, 477]], * Val accuracy / confusion: 72.37% / [[143, 87], [76, 284]] ------------------------------ Epoch 109 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.595578 - Iter 028 / 029, Loss: 0.659206 * Train accuracy / confusion: 76.72% / [[234, 130], [86, 478]], * Val accuracy / confusion: 71.19% / [[144, 86], [84, 276]] ------------------------------ Epoch 110 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.619570 - Iter 028 / 029, Loss: 0.403229 * Train accuracy / confusion: 75.65% / [[237, 126], [100, 465]], * Val accuracy / confusion: 71.69% / [[142, 88], [79, 281]] ------------------------------ Epoch 111 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.549087 - Iter 028 / 029, Loss: 0.457841 * Train accuracy / confusion: 76.83% / [[244, 119], [96, 469]], * Val accuracy / confusion: 73.22% / [[142, 88], [70, 290]] ------------------------------ Epoch 112 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.638257 - Iter 028 / 029, Loss: 0.437356 * Train accuracy / confusion: 78.02% / [[240, 120], [84, 484]], * Val accuracy / confusion: 76.10% / [[165, 65], [76, 284]] ------------------------------ Epoch 113 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.381537 - Iter 028 / 029, Loss: 0.432886 * Train accuracy / confusion: 76.40% / [[241, 122], [97, 468]], * Val accuracy / confusion: 72.54% / [[138, 92], [70, 290]] ------------------------------ Epoch 114 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.416929 - Iter 028 / 029, Loss: 0.442803 * Train accuracy / confusion: 76.72% / [[236, 124], [92, 476]], * Val accuracy / confusion: 73.73% / [[140, 90], [65, 295]] ------------------------------ Epoch 115 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.464661 - Iter 028 / 029, Loss: 0.424003 * Train accuracy / confusion: 76.08% / [[239, 121], [101, 467]], * Val accuracy / confusion: 68.47% / [[172, 58], [128, 232]] ------------------------------ Epoch 116 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.451057 - Iter 028 / 029, Loss: 0.377921 * Train accuracy / confusion: 77.26% / [[230, 132], [79, 487]], * Val accuracy / confusion: 75.08% / [[135, 95], [52, 308]] ------------------------------ Epoch 117 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.472479 - Iter 028 / 029, Loss: 0.433365 * Train accuracy / confusion: 75.75% / [[224, 137], [88, 479]], * Val accuracy / confusion: 70.34% / [[94, 136], [39, 321]] ------------------------------ Epoch 118 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.435057 - Iter 028 / 029, Loss: 0.380065 * Train accuracy / confusion: 77.59% / [[244, 116], [92, 476]], * Val accuracy / confusion: 70.00% / [[154, 76], [101, 259]] ------------------------------ Epoch 119 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.560581 - Iter 028 / 029, Loss: 0.461839 * Train accuracy / confusion: 77.05% / [[236, 122], [91, 479]], * Val accuracy / confusion: 74.41% / [[160, 70], [81, 279]] ------------------------------ Epoch 120 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.506981 - Iter 028 / 029, Loss: 0.402535 * Train accuracy / confusion: 76.51% / [[239, 121], [97, 471]], * Val accuracy / confusion: 73.05% / [[129, 101], [58, 302]] ------------------------------ Epoch 121 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.483489 - Iter 028 / 029, Loss: 0.401900 * Train accuracy / confusion: 75.75% / [[227, 137], [88, 476]], * Val accuracy / confusion: 72.88% / [[91, 139], [21, 339]] ------------------------------ Epoch 122 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.705050 - Iter 028 / 029, Loss: 0.695003 * Train accuracy / confusion: 76.72% / [[240, 120], [96, 472]], * Val accuracy / confusion: 71.86% / [[113, 117], [49, 311]] ------------------------------ Epoch 123 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.508961 - Iter 028 / 029, Loss: 0.570640 * Train accuracy / confusion: 76.19% / [[223, 138], [83, 484]], * Val accuracy / confusion: 76.78% / [[158, 72], [65, 295]] ------------------------------ Epoch 124 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.772940 - Iter 028 / 029, Loss: 0.424419 * Train accuracy / confusion: 76.94% / [[233, 129], [85, 481]], * Val accuracy / confusion: 70.68% / [[119, 111], [62, 298]] ------------------------------ Epoch 125 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.500803 - Iter 028 / 029, Loss: 0.727352 * Train accuracy / confusion: 77.48% / [[241, 117], [92, 478]], * Val accuracy / confusion: 73.22% / [[117, 113], [45, 315]] ------------------------------ Epoch 126 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.620007 - Iter 028 / 029, Loss: 0.403944 * Train accuracy / confusion: 78.02% / [[233, 129], [75, 491]], * Val accuracy / confusion: 70.34% / [[180, 50], [125, 235]] ------------------------------ Epoch 127 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.478410 - Iter 028 / 029, Loss: 0.587248 * Train accuracy / confusion: 77.16% / [[231, 126], [86, 485]], * Val accuracy / confusion: 73.56% / [[127, 103], [53, 307]] ------------------------------ Epoch 128 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.561236 - Iter 028 / 029, Loss: 0.339489 * Train accuracy / confusion: 76.40% / [[235, 128], [91, 474]], * Val accuracy / confusion: 74.41% / [[133, 97], [54, 306]] ------------------------------ Epoch 129 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.605398 - Iter 028 / 029, Loss: 0.425757 * Train accuracy / confusion: 78.02% / [[236, 127], [77, 488]], * Val accuracy / confusion: 74.07% / [[158, 72], [81, 279]] ------------------------------ Epoch 130 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.560980 - Iter 028 / 029, Loss: 0.533306 * Train accuracy / confusion: 77.26% / [[238, 124], [87, 479]], * Val accuracy / confusion: 74.58% / [[137, 93], [57, 303]] ------------------------------ Epoch 131 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.528121 - Iter 028 / 029, Loss: 0.417626 * Train accuracy / confusion: 78.02% / [[250, 111], [93, 474]], * Val accuracy / confusion: 73.56% / [[124, 106], [50, 310]] ------------------------------ Epoch 132 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.583281 - Iter 028 / 029, Loss: 0.490941 * Train accuracy / confusion: 76.08% / [[217, 146], [76, 489]], * Val accuracy / confusion: 77.63% / [[149, 81], [51, 309]] ------------------------------ Epoch 133 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.581132 - Iter 028 / 029, Loss: 0.451915 * Train accuracy / confusion: 76.40% / [[230, 131], [88, 479]], * Val accuracy / confusion: 73.90% / [[138, 92], [62, 298]] ------------------------------ Epoch 134 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.331982 - Iter 028 / 029, Loss: 0.510301 * Train accuracy / confusion: 76.62% / [[236, 121], [96, 475]], * Val accuracy / confusion: 73.05% / [[119, 111], [48, 312]] ------------------------------ Epoch 135 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.395582 - Iter 028 / 029, Loss: 0.413488 * Train accuracy / confusion: 78.56% / [[251, 114], [85, 478]], * Val accuracy / confusion: 73.39% / [[148, 82], [75, 285]] ------------------------------ Epoch 136 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.722721 - Iter 028 / 029, Loss: 0.455595 * Train accuracy / confusion: 75.86% / [[224, 139], [85, 480]], * Val accuracy / confusion: 75.42% / [[126, 104], [41, 319]] ------------------------------ Epoch 137 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.439782 - Iter 028 / 029, Loss: 0.526382 * Train accuracy / confusion: 78.23% / [[240, 120], [82, 486]], * Val accuracy / confusion: 74.41% / [[126, 104], [47, 313]] ------------------------------ Epoch 138 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.615071 - Iter 028 / 029, Loss: 0.471314 * Train accuracy / confusion: 76.40% / [[239, 124], [95, 470]], * Val accuracy / confusion: 75.25% / [[149, 81], [65, 295]] ------------------------------ Epoch 139 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.384660 - Iter 028 / 029, Loss: 0.476763 * Train accuracy / confusion: 77.16% / [[241, 121], [91, 475]], * Val accuracy / confusion: 73.56% / [[141, 89], [67, 293]] ------------------------------ Epoch 140 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.336796 - Iter 028 / 029, Loss: 0.468942 * Train accuracy / confusion: 77.48% / [[240, 119], [90, 479]], * Val accuracy / confusion: 75.42% / [[136, 94], [51, 309]] ------------------------------ Epoch 141 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.495659 - Iter 028 / 029, Loss: 0.475402 * Train accuracy / confusion: 77.59% / [[231, 130], [78, 489]], * Val accuracy / confusion: 74.41% / [[151, 79], [72, 288]] ------------------------------ Epoch 142 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.609001 - Iter 028 / 029, Loss: 0.441535 * Train accuracy / confusion: 77.05% / [[238, 123], [90, 477]], * Val accuracy / confusion: 72.88% / [[115, 115], [45, 315]] ------------------------------ Epoch 143 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.348874 - Iter 028 / 029, Loss: 0.384617 * Train accuracy / confusion: 76.29% / [[225, 132], [88, 483]], * Val accuracy / confusion: 73.73% / [[145, 85], [70, 290]] ------------------------------ Epoch 144 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.448006 - Iter 028 / 029, Loss: 0.684431 * Train accuracy / confusion: 77.69% / [[241, 120], [87, 480]], * Val accuracy / confusion: 72.03% / [[94, 136], [29, 331]] ------------------------------ Epoch 145 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.534127 - Iter 028 / 029, Loss: 0.647616 * Train accuracy / confusion: 76.83% / [[242, 118], [97, 471]], * Val accuracy / confusion: 75.42% / [[137, 93], [52, 308]] ------------------------------ Epoch 146 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.424306 - Iter 028 / 029, Loss: 0.507340 * Train accuracy / confusion: 78.23% / [[245, 116], [86, 481]], * Val accuracy / confusion: 74.07% / [[141, 89], [64, 296]] ------------------------------ Epoch 147 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.408590 - Iter 028 / 029, Loss: 0.452348 * Train accuracy / confusion: 76.08% / [[236, 125], [97, 470]], * Val accuracy / confusion: 73.56% / [[157, 73], [83, 277]] ------------------------------ Epoch 148 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.485251 - Iter 028 / 029, Loss: 0.405035 * Train accuracy / confusion: 78.34% / [[248, 116], [85, 479]], * Val accuracy / confusion: 73.39% / [[122, 108], [49, 311]] ------------------------------ Epoch 149 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.540212 - Iter 028 / 029, Loss: 0.571141 * Train accuracy / confusion: 76.29% / [[232, 135], [85, 476]], * Val accuracy / confusion: 75.42% / [[118, 112], [33, 327]] ------------------------------ Epoch 150 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.444837 - Iter 028 / 029, Loss: 0.412720 * Train accuracy / confusion: 78.66% / [[243, 116], [82, 487]], * Val accuracy / confusion: 72.54% / [[105, 125], [37, 323]] ------------------------------ Epoch 151 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.370250 - Iter 028 / 029, Loss: 0.552607 * Train accuracy / confusion: 78.02% / [[252, 111], [93, 472]], * Val accuracy / confusion: 74.41% / [[134, 96], [55, 305]] ------------------------------ Epoch 152 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.361072 - Iter 028 / 029, Loss: 0.740761 * Train accuracy / confusion: 77.69% / [[247, 116], [91, 474]], * Val accuracy / confusion: 74.41% / [[159, 71], [80, 280]] ------------------------------ Epoch 153 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.372104 - Iter 028 / 029, Loss: 0.656934 * Train accuracy / confusion: 77.37% / [[247, 114], [96, 471]], * Val accuracy / confusion: 74.92% / [[125, 105], [43, 317]] ------------------------------ Epoch 154 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.366243 - Iter 028 / 029, Loss: 0.404189 * Train accuracy / confusion: 78.45% / [[255, 109], [91, 473]], * Val accuracy / confusion: 67.63% / [[71, 159], [32, 328]] ------------------------------ Epoch 155 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.298185 - Iter 028 / 029, Loss: 0.623718 * Train accuracy / confusion: 78.77% / [[248, 110], [87, 483]], * Val accuracy / confusion: 73.73% / [[154, 76], [79, 281]] ------------------------------ Epoch 156 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.471416 - Iter 028 / 029, Loss: 0.548182 * Train accuracy / confusion: 76.40% / [[240, 125], [94, 469]], * Val accuracy / confusion: 73.56% / [[147, 83], [73, 287]] ------------------------------ Epoch 157 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.489675 - Iter 028 / 029, Loss: 0.449068 * Train accuracy / confusion: 77.69% / [[249, 113], [94, 472]], * Val accuracy / confusion: 71.53% / [[164, 66], [102, 258]] ------------------------------ Epoch 158 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.469806 - Iter 028 / 029, Loss: 0.592261 * Train accuracy / confusion: 76.29% / [[231, 132], [88, 477]], * Val accuracy / confusion: 74.24% / [[110, 120], [32, 328]] ------------------------------ Epoch 159 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.362752 - Iter 028 / 029, Loss: 0.464650 * Train accuracy / confusion: 76.94% / [[235, 130], [84, 479]], * Val accuracy / confusion: 74.58% / [[131, 99], [51, 309]] ------------------------------ Epoch 160 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.511036 - Iter 028 / 029, Loss: 0.282708 * Train accuracy / confusion: 80.28% / [[266, 95], [88, 479]], * Val accuracy / confusion: 73.56% / [[123, 107], [49, 311]] ------------------------------ Epoch 161 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.509213 - Iter 028 / 029, Loss: 0.305244 * Train accuracy / confusion: 77.26% / [[228, 133], [78, 489]], * Val accuracy / confusion: 72.88% / [[120, 110], [50, 310]] ------------------------------ Epoch 162 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.455242 - Iter 028 / 029, Loss: 0.379976 * Train accuracy / confusion: 78.77% / [[236, 124], [73, 495]], * Val accuracy / confusion: 71.19% / [[153, 77], [93, 267]] ------------------------------ Epoch 163 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.374814 - Iter 028 / 029, Loss: 0.312493 * Train accuracy / confusion: 77.91% / [[245, 118], [87, 478]], * Val accuracy / confusion: 71.19% / [[171, 59], [111, 249]] ------------------------------ Epoch 164 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.457238 - Iter 028 / 029, Loss: 0.382112 * Train accuracy / confusion: 77.80% / [[240, 122], [84, 482]], * Val accuracy / confusion: 73.56% / [[143, 87], [69, 291]] ------------------------------ Epoch 165 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.569810 - Iter 028 / 029, Loss: 0.416103 * Train accuracy / confusion: 77.16% / [[235, 123], [89, 481]], * Val accuracy / confusion: 76.10% / [[134, 96], [45, 315]] ------------------------------ Epoch 166 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.471684 - Iter 028 / 029, Loss: 0.411750 * Train accuracy / confusion: 77.80% / [[235, 129], [77, 487]], * Val accuracy / confusion: 73.73% / [[146, 84], [71, 289]] ------------------------------ Epoch 167 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.535820 - Iter 028 / 029, Loss: 0.384668 * Train accuracy / confusion: 78.23% / [[247, 116], [86, 479]], * Val accuracy / confusion: 72.03% / [[147, 83], [82, 278]] ------------------------------ Epoch 168 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.460160 - Iter 028 / 029, Loss: 0.660992 * Train accuracy / confusion: 78.77% / [[253, 112], [85, 478]], * Val accuracy / confusion: 75.25% / [[174, 56], [90, 270]] ------------------------------ Epoch 169 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.403696 - Iter 028 / 029, Loss: 0.424048 * Train accuracy / confusion: 77.69% / [[243, 119], [88, 478]], * Val accuracy / confusion: 74.75% / [[158, 72], [77, 283]] ------------------------------ Epoch 170 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.548367 - Iter 028 / 029, Loss: 0.270638 * Train accuracy / confusion: 78.66% / [[253, 109], [89, 477]], * Val accuracy / confusion: 73.90% / [[124, 106], [48, 312]] ------------------------------ Epoch 171 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.525249 - Iter 028 / 029, Loss: 0.526564 * Train accuracy / confusion: 77.91% / [[254, 108], [97, 469]], * Val accuracy / confusion: 75.08% / [[119, 111], [36, 324]] ------------------------------ Epoch 172 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.556750 - Iter 028 / 029, Loss: 0.479291 * Train accuracy / confusion: 77.69% / [[245, 116], [91, 476]], * Val accuracy / confusion: 73.39% / [[173, 57], [100, 260]] ------------------------------ Epoch 173 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.677837 - Iter 028 / 029, Loss: 0.472429 * Train accuracy / confusion: 78.45% / [[262, 101], [99, 466]], * Val accuracy / confusion: 76.44% / [[146, 84], [55, 305]] ------------------------------ Epoch 174 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.367366 - Iter 028 / 029, Loss: 0.396452 * Train accuracy / confusion: 77.48% / [[243, 119], [90, 476]], * Val accuracy / confusion: 72.03% / [[167, 63], [102, 258]] ------------------------------ Epoch 175 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.517922 - Iter 028 / 029, Loss: 0.492286 * Train accuracy / confusion: 77.91% / [[249, 111], [94, 474]], * Val accuracy / confusion: 73.39% / [[132, 98], [59, 301]] ------------------------------ Epoch 176 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.351309 - Iter 028 / 029, Loss: 0.434487 * Train accuracy / confusion: 77.59% / [[241, 120], [88, 479]], * Val accuracy / confusion: 73.05% / [[190, 40], [119, 241]] ------------------------------ Epoch 177 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.591432 - Iter 028 / 029, Loss: 0.325661 * Train accuracy / confusion: 78.23% / [[251, 109], [93, 475]], * Val accuracy / confusion: 74.41% / [[142, 88], [63, 297]] ------------------------------ Epoch 178 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.477586 - Iter 028 / 029, Loss: 0.403228 * Train accuracy / confusion: 76.83% / [[234, 127], [88, 479]], * Val accuracy / confusion: 70.68% / [[134, 96], [77, 283]] ------------------------------ Epoch 179 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.326953 - Iter 028 / 029, Loss: 0.604462 * Train accuracy / confusion: 78.02% / [[255, 106], [98, 469]], * Val accuracy / confusion: 71.69% / [[93, 137], [30, 330]] ------------------------------ Epoch 180 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.467487 - Iter 028 / 029, Loss: 0.491397 * Train accuracy / confusion: 79.31% / [[254, 110], [82, 482]], * Val accuracy / confusion: 76.61% / [[145, 85], [53, 307]] ------------------------------ Epoch 181 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.673740 - Iter 028 / 029, Loss: 0.394626 * Train accuracy / confusion: 79.63% / [[268, 96], [93, 471]], * Val accuracy / confusion: 71.19% / [[162, 68], [102, 258]] ------------------------------ Epoch 182 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.565780 - Iter 028 / 029, Loss: 0.494939 * Train accuracy / confusion: 78.23% / [[252, 107], [95, 474]], * Val accuracy / confusion: 73.73% / [[110, 120], [35, 325]] ------------------------------ Epoch 183 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.419849 - Iter 028 / 029, Loss: 0.569889 * Train accuracy / confusion: 79.09% / [[244, 119], [75, 490]], * Val accuracy / confusion: 72.03% / [[129, 101], [64, 296]] ------------------------------ Epoch 184 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.512066 - Iter 028 / 029, Loss: 0.369984 * Train accuracy / confusion: 78.66% / [[253, 112], [86, 477]], * Val accuracy / confusion: 73.90% / [[151, 79], [75, 285]] ------------------------------ Epoch 185 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.452613 - Iter 028 / 029, Loss: 0.394745 * Train accuracy / confusion: 79.31% / [[246, 114], [78, 490]], * Val accuracy / confusion: 72.37% / [[142, 88], [75, 285]] ------------------------------ Epoch 186 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.416434 - Iter 028 / 029, Loss: 0.408035 * Train accuracy / confusion: 78.66% / [[248, 114], [84, 482]], * Val accuracy / confusion: 73.56% / [[130, 100], [56, 304]] ------------------------------ Epoch 187 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.482336 - Iter 028 / 029, Loss: 0.664454 * Train accuracy / confusion: 78.77% / [[249, 112], [85, 482]], * Val accuracy / confusion: 73.22% / [[145, 85], [73, 287]] ------------------------------ Epoch 188 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.504960 - Iter 028 / 029, Loss: 0.496913 * Train accuracy / confusion: 77.26% / [[242, 120], [91, 475]], * Val accuracy / confusion: 73.22% / [[108, 122], [36, 324]] ------------------------------ Epoch 189 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.396150 - Iter 028 / 029, Loss: 0.589513 * Train accuracy / confusion: 77.69% / [[249, 112], [95, 472]], * Val accuracy / confusion: 74.24% / [[128, 102], [50, 310]] ------------------------------ Epoch 190 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.604021 - Iter 028 / 029, Loss: 0.472241 * Train accuracy / confusion: 77.69% / [[238, 127], [80, 483]], * Val accuracy / confusion: 74.41% / [[142, 88], [63, 297]] ------------------------------ Epoch 191 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.397967 - Iter 028 / 029, Loss: 0.489856 * Train accuracy / confusion: 77.26% / [[253, 107], [104, 464]], * Val accuracy / confusion: 75.25% / [[148, 82], [64, 296]] ------------------------------ Epoch 192 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.528833 - Iter 028 / 029, Loss: 0.434606 * Train accuracy / confusion: 78.66% / [[236, 126], [72, 494]], * Val accuracy / confusion: 72.54% / [[121, 109], [53, 307]] ------------------------------ Epoch 193 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.619281 - Iter 028 / 029, Loss: 0.500056 * Train accuracy / confusion: 78.88% / [[254, 107], [89, 478]], * Val accuracy / confusion: 70.85% / [[175, 55], [117, 243]] ------------------------------ Epoch 194 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.347188 - Iter 028 / 029, Loss: 0.475800 * Train accuracy / confusion: 76.51% / [[244, 123], [95, 466]], * Val accuracy / confusion: 74.07% / [[120, 110], [43, 317]] ------------------------------ Epoch 195 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.394905 - Iter 028 / 029, Loss: 0.565647 * Train accuracy / confusion: 79.42% / [[265, 99], [92, 472]], * Val accuracy / confusion: 71.53% / [[138, 92], [76, 284]] ------------------------------ Epoch 196 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.558701 - Iter 028 / 029, Loss: 0.355482 * Train accuracy / confusion: 78.45% / [[236, 126], [74, 492]], * Val accuracy / confusion: 71.86% / [[122, 108], [58, 302]] ------------------------------ Epoch 197 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.383869 - Iter 028 / 029, Loss: 0.513819 * Train accuracy / confusion: 79.85% / [[250, 111], [76, 491]], * Val accuracy / confusion: 74.58% / [[133, 97], [53, 307]] ------------------------------ Epoch 198 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.596919 - Iter 028 / 029, Loss: 0.424546 * Train accuracy / confusion: 78.56% / [[241, 118], [81, 488]], * Val accuracy / confusion: 72.71% / [[148, 82], [79, 281]] ------------------------------ Epoch 199 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.419300 - Iter 028 / 029, Loss: 0.313507 * Train accuracy / confusion: 78.99% / [[246, 114], [81, 487]], * Val accuracy / confusion: 71.69% / [[98, 132], [35, 325]] ------------------------------ Epoch 200 / 500, Learning rate: 2.75e-03 ------------------------------ - Iter 014 / 029, Loss: 0.330821 - Iter 028 / 029, Loss: 0.716350 * Train accuracy / confusion: 78.77% / [[251, 112], [85, 480]], * Val accuracy / confusion: 74.75% / [[139, 91], [58, 302]] ------------------------------ Epoch 201 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.497844 - Iter 028 / 029, Loss: 0.434931 * Train accuracy / confusion: 79.53% / [[243, 117], [73, 495]], * Val accuracy / confusion: 74.92% / [[130, 100], [48, 312]] ------------------------------ Epoch 202 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.293996 - Iter 028 / 029, Loss: 0.660517 * Train accuracy / confusion: 80.60% / [[250, 116], [64, 498]], * Val accuracy / confusion: 73.39% / [[133, 97], [60, 300]] ------------------------------ Epoch 203 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.475512 - Iter 028 / 029, Loss: 0.481828 * Train accuracy / confusion: 79.74% / [[250, 113], [75, 490]], * Val accuracy / confusion: 73.73% / [[134, 96], [59, 301]] ------------------------------ Epoch 204 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.413217 - Iter 028 / 029, Loss: 0.454396 * Train accuracy / confusion: 77.48% / [[237, 122], [87, 482]], * Val accuracy / confusion: 72.71% / [[134, 96], [65, 295]] ------------------------------ Epoch 205 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.442066 - Iter 028 / 029, Loss: 0.426826 * Train accuracy / confusion: 80.50% / [[254, 109], [72, 493]], * Val accuracy / confusion: 74.75% / [[122, 108], [41, 319]] ------------------------------ Epoch 206 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.395565 - Iter 028 / 029, Loss: 0.428691 * Train accuracy / confusion: 80.82% / [[252, 109], [69, 498]], * Val accuracy / confusion: 73.73% / [[138, 92], [63, 297]] ------------------------------ Epoch 207 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.297401 - Iter 028 / 029, Loss: 0.446413 * Train accuracy / confusion: 77.91% / [[237, 127], [78, 486]], * Val accuracy / confusion: 73.56% / [[135, 95], [61, 299]] ------------------------------ Epoch 208 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.337365 - Iter 028 / 029, Loss: 0.634970 * Train accuracy / confusion: 79.53% / [[253, 111], [79, 485]], * Val accuracy / confusion: 73.73% / [[136, 94], [61, 299]] ------------------------------ Epoch 209 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.287147 - Iter 028 / 029, Loss: 0.414288 * Train accuracy / confusion: 80.17% / [[256, 106], [78, 488]], * Val accuracy / confusion: 74.75% / [[144, 86], [63, 297]] ------------------------------ Epoch 210 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.430025 - Iter 028 / 029, Loss: 0.413695 * Train accuracy / confusion: 80.82% / [[255, 107], [71, 495]], * Val accuracy / confusion: 72.37% / [[134, 96], [67, 293]] ------------------------------ Epoch 211 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.340724 - Iter 028 / 029, Loss: 0.338228 * Train accuracy / confusion: 80.60% / [[255, 106], [74, 493]], * Val accuracy / confusion: 72.88% / [[141, 89], [71, 289]] ------------------------------ Epoch 212 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.456886 - Iter 028 / 029, Loss: 0.436284 * Train accuracy / confusion: 79.42% / [[251, 112], [79, 486]], * Val accuracy / confusion: 71.36% / [[127, 103], [66, 294]] ------------------------------ Epoch 213 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.517967 - Iter 028 / 029, Loss: 0.422324 * Train accuracy / confusion: 80.06% / [[253, 109], [76, 490]], * Val accuracy / confusion: 73.39% / [[130, 100], [57, 303]] ------------------------------ Epoch 214 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.565128 - Iter 028 / 029, Loss: 0.371108 * Train accuracy / confusion: 79.63% / [[254, 108], [81, 485]], * Val accuracy / confusion: 71.69% / [[133, 97], [70, 290]] ------------------------------ Epoch 215 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.321977 - Iter 028 / 029, Loss: 0.255224 * Train accuracy / confusion: 79.42% / [[246, 115], [76, 491]], * Val accuracy / confusion: 73.56% / [[134, 96], [60, 300]] ------------------------------ Epoch 216 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.408022 - Iter 028 / 029, Loss: 0.672179 * Train accuracy / confusion: 79.85% / [[255, 109], [78, 486]], * Val accuracy / confusion: 74.41% / [[141, 89], [62, 298]] ------------------------------ Epoch 217 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.412292 - Iter 028 / 029, Loss: 0.502716 * Train accuracy / confusion: 80.71% / [[259, 102], [77, 490]], * Val accuracy / confusion: 71.53% / [[128, 102], [66, 294]] ------------------------------ Epoch 218 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.489903 - Iter 028 / 029, Loss: 0.538449 * Train accuracy / confusion: 80.17% / [[247, 114], [70, 497]], * Val accuracy / confusion: 71.53% / [[133, 97], [71, 289]] ------------------------------ Epoch 219 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.475273 - Iter 028 / 029, Loss: 0.417306 * Train accuracy / confusion: 79.63% / [[250, 112], [77, 489]], * Val accuracy / confusion: 72.03% / [[123, 107], [58, 302]] ------------------------------ Epoch 220 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.384135 - Iter 028 / 029, Loss: 0.405227 * Train accuracy / confusion: 81.79% / [[261, 100], [69, 498]], * Val accuracy / confusion: 72.54% / [[135, 95], [67, 293]] ------------------------------ Epoch 221 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.335834 - Iter 028 / 029, Loss: 0.543697 * Train accuracy / confusion: 80.06% / [[251, 111], [74, 492]], * Val accuracy / confusion: 73.56% / [[137, 93], [63, 297]] ------------------------------ Epoch 222 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.415667 - Iter 028 / 029, Loss: 0.580464 * Train accuracy / confusion: 79.74% / [[250, 116], [72, 490]], * Val accuracy / confusion: 72.88% / [[139, 91], [69, 291]] ------------------------------ Epoch 223 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.304027 - Iter 028 / 029, Loss: 0.382554 * Train accuracy / confusion: 80.93% / [[260, 101], [76, 491]], * Val accuracy / confusion: 73.22% / [[145, 85], [73, 287]] ------------------------------ Epoch 224 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.422501 - Iter 028 / 029, Loss: 0.696684 * Train accuracy / confusion: 80.28% / [[253, 106], [77, 492]], * Val accuracy / confusion: 72.88% / [[139, 91], [69, 291]] ------------------------------ Epoch 225 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.436782 - Iter 028 / 029, Loss: 0.583620 * Train accuracy / confusion: 80.17% / [[250, 112], [72, 494]], * Val accuracy / confusion: 72.88% / [[145, 85], [75, 285]] ------------------------------ Epoch 226 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.322988 - Iter 028 / 029, Loss: 0.347303 * Train accuracy / confusion: 79.74% / [[251, 105], [83, 489]], * Val accuracy / confusion: 73.39% / [[132, 98], [59, 301]] ------------------------------ Epoch 227 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.305937 - Iter 028 / 029, Loss: 0.296927 * Train accuracy / confusion: 80.39% / [[260, 103], [79, 486]], * Val accuracy / confusion: 72.88% / [[133, 97], [63, 297]] ------------------------------ Epoch 228 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.339458 - Iter 028 / 029, Loss: 0.417303 * Train accuracy / confusion: 79.74% / [[257, 107], [81, 483]], * Val accuracy / confusion: 72.54% / [[133, 97], [65, 295]] ------------------------------ Epoch 229 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.481209 - Iter 028 / 029, Loss: 0.354556 * Train accuracy / confusion: 79.20% / [[256, 107], [86, 479]], * Val accuracy / confusion: 73.90% / [[144, 86], [68, 292]] ------------------------------ Epoch 230 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.288418 - Iter 028 / 029, Loss: 0.539193 * Train accuracy / confusion: 78.99% / [[250, 113], [82, 483]], * Val accuracy / confusion: 73.22% / [[149, 81], [77, 283]] ------------------------------ Epoch 231 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.295259 - Iter 028 / 029, Loss: 0.420586 * Train accuracy / confusion: 81.57% / [[263, 100], [71, 494]], * Val accuracy / confusion: 69.66% / [[122, 108], [71, 289]] ------------------------------ Epoch 232 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.303591 - Iter 028 / 029, Loss: 0.483818 * Train accuracy / confusion: 81.36% / [[264, 97], [76, 491]], * Val accuracy / confusion: 71.36% / [[133, 97], [72, 288]] ------------------------------ Epoch 233 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.261111 - Iter 028 / 029, Loss: 0.301642 * Train accuracy / confusion: 80.60% / [[257, 102], [78, 491]], * Val accuracy / confusion: 75.25% / [[141, 89], [57, 303]] ------------------------------ Epoch 234 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.293958 - Iter 028 / 029, Loss: 0.302030 * Train accuracy / confusion: 80.93% / [[255, 107], [70, 496]], * Val accuracy / confusion: 70.68% / [[128, 102], [71, 289]] ------------------------------ Epoch 235 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.548640 - Iter 028 / 029, Loss: 0.368967 * Train accuracy / confusion: 79.31% / [[254, 107], [85, 482]], * Val accuracy / confusion: 73.39% / [[140, 90], [67, 293]] ------------------------------ Epoch 236 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.368450 - Iter 028 / 029, Loss: 0.562543 * Train accuracy / confusion: 81.36% / [[261, 101], [72, 494]], * Val accuracy / confusion: 71.19% / [[135, 95], [75, 285]] ------------------------------ Epoch 237 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.581676 - Iter 028 / 029, Loss: 0.323653 * Train accuracy / confusion: 80.50% / [[258, 105], [76, 489]], * Val accuracy / confusion: 73.22% / [[134, 96], [62, 298]] ------------------------------ Epoch 238 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.342460 - Iter 028 / 029, Loss: 0.580279 * Train accuracy / confusion: 78.88% / [[247, 113], [83, 485]], * Val accuracy / confusion: 71.86% / [[129, 101], [65, 295]] ------------------------------ Epoch 239 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.423511 - Iter 028 / 029, Loss: 0.574282 * Train accuracy / confusion: 80.39% / [[258, 103], [79, 488]], * Val accuracy / confusion: 73.56% / [[143, 87], [69, 291]] ------------------------------ Epoch 240 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.403400 - Iter 028 / 029, Loss: 0.425950 * Train accuracy / confusion: 79.74% / [[254, 111], [77, 486]], * Val accuracy / confusion: 72.54% / [[132, 98], [64, 296]] ------------------------------ Epoch 241 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.483575 - Iter 028 / 029, Loss: 0.463714 * Train accuracy / confusion: 79.31% / [[251, 109], [83, 485]], * Val accuracy / confusion: 73.56% / [[136, 94], [62, 298]] ------------------------------ Epoch 242 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.424317 - Iter 028 / 029, Loss: 0.366792 * Train accuracy / confusion: 81.47% / [[261, 104], [68, 495]], * Val accuracy / confusion: 71.69% / [[127, 103], [64, 296]] ------------------------------ Epoch 243 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.369160 - Iter 028 / 029, Loss: 0.330990 * Train accuracy / confusion: 82.00% / [[266, 99], [68, 495]], * Val accuracy / confusion: 72.20% / [[133, 97], [67, 293]] ------------------------------ Epoch 244 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.618119 - Iter 028 / 029, Loss: 0.324272 * Train accuracy / confusion: 78.99% / [[248, 118], [77, 485]], * Val accuracy / confusion: 72.37% / [[135, 95], [68, 292]] ------------------------------ Epoch 245 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.586996 - Iter 028 / 029, Loss: 0.566326 * Train accuracy / confusion: 79.85% / [[253, 109], [78, 488]], * Val accuracy / confusion: 71.19% / [[142, 88], [82, 278]] ------------------------------ Epoch 246 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.598151 - Iter 028 / 029, Loss: 0.353398 * Train accuracy / confusion: 79.85% / [[252, 112], [75, 489]], * Val accuracy / confusion: 71.86% / [[144, 86], [80, 280]] ------------------------------ Epoch 247 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.408496 - Iter 028 / 029, Loss: 0.456178 * Train accuracy / confusion: 79.96% / [[255, 106], [80, 487]], * Val accuracy / confusion: 72.37% / [[140, 90], [73, 287]] ------------------------------ Epoch 248 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.309713 - Iter 028 / 029, Loss: 0.420113 * Train accuracy / confusion: 81.79% / [[257, 105], [64, 502]], * Val accuracy / confusion: 72.88% / [[128, 102], [58, 302]] ------------------------------ Epoch 249 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.493357 - Iter 028 / 029, Loss: 0.322164 * Train accuracy / confusion: 81.57% / [[262, 98], [73, 495]], * Val accuracy / confusion: 73.56% / [[139, 91], [65, 295]] ------------------------------ Epoch 250 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.352883 - Iter 028 / 029, Loss: 0.553026 * Train accuracy / confusion: 80.82% / [[255, 105], [73, 495]], * Val accuracy / confusion: 73.05% / [[137, 93], [66, 294]] ------------------------------ Epoch 251 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.449805 - Iter 028 / 029, Loss: 0.457922 * Train accuracy / confusion: 81.14% / [[258, 102], [73, 495]], * Val accuracy / confusion: 72.37% / [[140, 90], [73, 287]] ------------------------------ Epoch 252 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.584821 - Iter 028 / 029, Loss: 0.398020 * Train accuracy / confusion: 81.68% / [[264, 97], [73, 494]], * Val accuracy / confusion: 75.42% / [[147, 83], [62, 298]] ------------------------------ Epoch 253 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.310453 - Iter 028 / 029, Loss: 0.313847 * Train accuracy / confusion: 79.96% / [[259, 108], [78, 483]], * Val accuracy / confusion: 72.20% / [[132, 98], [66, 294]] ------------------------------ Epoch 254 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.486276 - Iter 028 / 029, Loss: 0.405329 * Train accuracy / confusion: 81.90% / [[264, 98], [70, 496]], * Val accuracy / confusion: 70.00% / [[127, 103], [74, 286]] ------------------------------ Epoch 255 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.386976 - Iter 028 / 029, Loss: 0.460820 * Train accuracy / confusion: 81.14% / [[257, 107], [68, 496]], * Val accuracy / confusion: 72.20% / [[139, 91], [73, 287]] ------------------------------ Epoch 256 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.273080 - Iter 028 / 029, Loss: 0.435536 * Train accuracy / confusion: 81.47% / [[263, 98], [74, 493]], * Val accuracy / confusion: 74.41% / [[137, 93], [58, 302]] ------------------------------ Epoch 257 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.403889 - Iter 028 / 029, Loss: 0.587358 * Train accuracy / confusion: 79.63% / [[251, 110], [79, 488]], * Val accuracy / confusion: 73.73% / [[138, 92], [63, 297]] ------------------------------ Epoch 258 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.382473 - Iter 028 / 029, Loss: 0.370444 * Train accuracy / confusion: 79.96% / [[253, 111], [75, 489]], * Val accuracy / confusion: 70.85% / [[140, 90], [82, 278]] ------------------------------ Epoch 259 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.413895 - Iter 028 / 029, Loss: 0.365216 * Train accuracy / confusion: 80.93% / [[256, 106], [71, 495]], * Val accuracy / confusion: 73.05% / [[145, 85], [74, 286]] ------------------------------ Epoch 260 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.408899 - Iter 028 / 029, Loss: 0.372434 * Train accuracy / confusion: 79.20% / [[251, 110], [83, 484]], * Val accuracy / confusion: 72.20% / [[130, 100], [64, 296]] ------------------------------ Epoch 261 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.431988 - Iter 028 / 029, Loss: 0.372124 * Train accuracy / confusion: 80.50% / [[254, 107], [74, 493]], * Val accuracy / confusion: 73.05% / [[140, 90], [69, 291]] ------------------------------ Epoch 262 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.458662 - Iter 028 / 029, Loss: 0.612629 * Train accuracy / confusion: 82.65% / [[266, 96], [65, 501]], * Val accuracy / confusion: 74.41% / [[141, 89], [62, 298]] ------------------------------ Epoch 263 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.387324 - Iter 028 / 029, Loss: 0.338522 * Train accuracy / confusion: 80.93% / [[257, 103], [74, 494]], * Val accuracy / confusion: 74.41% / [[143, 87], [64, 296]] ------------------------------ Epoch 264 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.426846 - Iter 028 / 029, Loss: 0.482811 * Train accuracy / confusion: 81.25% / [[253, 105], [69, 501]], * Val accuracy / confusion: 72.03% / [[141, 89], [76, 284]] ------------------------------ Epoch 265 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.440405 - Iter 028 / 029, Loss: 0.274789 * Train accuracy / confusion: 81.79% / [[262, 99], [70, 497]], * Val accuracy / confusion: 74.07% / [[135, 95], [58, 302]] ------------------------------ Epoch 266 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.321360 - Iter 028 / 029, Loss: 0.369722 * Train accuracy / confusion: 81.47% / [[256, 105], [67, 500]], * Val accuracy / confusion: 73.39% / [[135, 95], [62, 298]] ------------------------------ Epoch 267 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.334689 - Iter 028 / 029, Loss: 0.440808 * Train accuracy / confusion: 80.93% / [[262, 100], [77, 489]], * Val accuracy / confusion: 73.90% / [[148, 82], [72, 288]] ------------------------------ Epoch 268 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.570910 - Iter 028 / 029, Loss: 0.474815 * Train accuracy / confusion: 79.74% / [[254, 102], [86, 486]], * Val accuracy / confusion: 73.05% / [[145, 85], [74, 286]] ------------------------------ Epoch 269 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.545338 - Iter 028 / 029, Loss: 0.587368 * Train accuracy / confusion: 80.50% / [[257, 101], [80, 490]], * Val accuracy / confusion: 73.22% / [[144, 86], [72, 288]] ------------------------------ Epoch 270 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.359212 - Iter 028 / 029, Loss: 0.448548 * Train accuracy / confusion: 81.90% / [[266, 96], [72, 494]], * Val accuracy / confusion: 73.22% / [[132, 98], [60, 300]] ------------------------------ Epoch 271 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.616089 - Iter 028 / 029, Loss: 0.427669 * Train accuracy / confusion: 81.79% / [[262, 99], [70, 497]], * Val accuracy / confusion: 71.86% / [[137, 93], [73, 287]] ------------------------------ Epoch 272 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.309798 - Iter 028 / 029, Loss: 0.376248 * Train accuracy / confusion: 80.28% / [[263, 102], [81, 482]], * Val accuracy / confusion: 72.54% / [[141, 89], [73, 287]] ------------------------------ Epoch 273 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.284430 - Iter 028 / 029, Loss: 0.475884 * Train accuracy / confusion: 80.82% / [[260, 101], [77, 490]], * Val accuracy / confusion: 74.07% / [[149, 81], [72, 288]] ------------------------------ Epoch 274 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.637052 - Iter 028 / 029, Loss: 0.400380 * Train accuracy / confusion: 80.71% / [[252, 107], [72, 497]], * Val accuracy / confusion: 72.20% / [[143, 87], [77, 283]] ------------------------------ Epoch 275 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.445379 - Iter 028 / 029, Loss: 0.690304 * Train accuracy / confusion: 79.53% / [[253, 110], [80, 485]], * Val accuracy / confusion: 73.22% / [[144, 86], [72, 288]] ------------------------------ Epoch 276 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.614318 - Iter 028 / 029, Loss: 0.427903 * Train accuracy / confusion: 80.60% / [[257, 101], [79, 491]], * Val accuracy / confusion: 72.37% / [[135, 95], [68, 292]] ------------------------------ Epoch 277 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.579139 - Iter 028 / 029, Loss: 0.424818 * Train accuracy / confusion: 80.71% / [[260, 101], [78, 489]], * Val accuracy / confusion: 71.69% / [[134, 96], [71, 289]] ------------------------------ Epoch 278 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.420949 - Iter 028 / 029, Loss: 0.361620 * Train accuracy / confusion: 81.90% / [[268, 87], [81, 492]], * Val accuracy / confusion: 71.02% / [[137, 93], [78, 282]] ------------------------------ Epoch 279 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.260656 - Iter 028 / 029, Loss: 0.416738 * Train accuracy / confusion: 80.50% / [[258, 101], [80, 489]], * Val accuracy / confusion: 72.03% / [[135, 95], [70, 290]] ------------------------------ Epoch 280 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.504265 - Iter 028 / 029, Loss: 0.637332 * Train accuracy / confusion: 81.57% / [[258, 105], [66, 499]], * Val accuracy / confusion: 71.19% / [[138, 92], [78, 282]] ------------------------------ Epoch 281 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.356502 - Iter 028 / 029, Loss: 0.438190 * Train accuracy / confusion: 83.08% / [[269, 93], [64, 502]], * Val accuracy / confusion: 72.71% / [[136, 94], [67, 293]] ------------------------------ Epoch 282 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.373236 - Iter 028 / 029, Loss: 0.366292 * Train accuracy / confusion: 81.79% / [[268, 93], [76, 491]], * Val accuracy / confusion: 72.37% / [[157, 73], [90, 270]] ------------------------------ Epoch 283 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.412539 - Iter 028 / 029, Loss: 0.445665 * Train accuracy / confusion: 80.17% / [[255, 107], [77, 489]], * Val accuracy / confusion: 72.37% / [[135, 95], [68, 292]] ------------------------------ Epoch 284 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.574320 - Iter 028 / 029, Loss: 0.288466 * Train accuracy / confusion: 79.31% / [[254, 109], [83, 482]], * Val accuracy / confusion: 70.00% / [[151, 79], [98, 262]] ------------------------------ Epoch 285 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.487692 - Iter 028 / 029, Loss: 0.336554 * Train accuracy / confusion: 77.91% / [[246, 114], [91, 477]], * Val accuracy / confusion: 73.22% / [[135, 95], [63, 297]] ------------------------------ Epoch 286 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.448271 - Iter 028 / 029, Loss: 0.338136 * Train accuracy / confusion: 81.79% / [[258, 103], [66, 501]], * Val accuracy / confusion: 72.37% / [[131, 99], [64, 296]] ------------------------------ Epoch 287 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.565276 - Iter 028 / 029, Loss: 0.485924 * Train accuracy / confusion: 78.88% / [[252, 113], [83, 480]], * Val accuracy / confusion: 72.88% / [[140, 90], [70, 290]] ------------------------------ Epoch 288 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.460973 - Iter 028 / 029, Loss: 0.378190 * Train accuracy / confusion: 81.90% / [[264, 95], [73, 496]], * Val accuracy / confusion: 74.92% / [[136, 94], [54, 306]] ------------------------------ Epoch 289 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.330646 - Iter 028 / 029, Loss: 0.414268 * Train accuracy / confusion: 80.60% / [[256, 106], [74, 492]], * Val accuracy / confusion: 73.39% / [[135, 95], [62, 298]] ------------------------------ Epoch 290 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.400722 - Iter 028 / 029, Loss: 0.430411 * Train accuracy / confusion: 81.36% / [[261, 101], [72, 494]], * Val accuracy / confusion: 73.39% / [[144, 86], [71, 289]] ------------------------------ Epoch 291 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.427378 - Iter 028 / 029, Loss: 0.312096 * Train accuracy / confusion: 81.03% / [[257, 108], [68, 495]], * Val accuracy / confusion: 71.02% / [[140, 90], [81, 279]] ------------------------------ Epoch 292 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.335644 - Iter 028 / 029, Loss: 0.478543 * Train accuracy / confusion: 80.39% / [[262, 100], [82, 484]], * Val accuracy / confusion: 72.54% / [[142, 88], [74, 286]] ------------------------------ Epoch 293 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.281949 - Iter 028 / 029, Loss: 0.385843 * Train accuracy / confusion: 81.03% / [[264, 103], [73, 488]], * Val accuracy / confusion: 73.05% / [[143, 87], [72, 288]] ------------------------------ Epoch 294 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.447175 - Iter 028 / 029, Loss: 0.456707 * Train accuracy / confusion: 82.87% / [[272, 95], [64, 497]], * Val accuracy / confusion: 73.73% / [[145, 85], [70, 290]] ------------------------------ Epoch 295 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.294075 - Iter 028 / 029, Loss: 0.467073 * Train accuracy / confusion: 81.25% / [[260, 98], [76, 494]], * Val accuracy / confusion: 72.71% / [[134, 96], [65, 295]] ------------------------------ Epoch 296 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.320081 - Iter 028 / 029, Loss: 0.466752 * Train accuracy / confusion: 80.93% / [[261, 100], [77, 490]], * Val accuracy / confusion: 74.41% / [[144, 86], [65, 295]] ------------------------------ Epoch 297 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.345942 - Iter 028 / 029, Loss: 0.446645 * Train accuracy / confusion: 79.53% / [[251, 109], [81, 487]], * Val accuracy / confusion: 73.56% / [[138, 92], [64, 296]] ------------------------------ Epoch 298 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.327232 - Iter 028 / 029, Loss: 0.487020 * Train accuracy / confusion: 81.68% / [[263, 102], [68, 495]], * Val accuracy / confusion: 72.20% / [[130, 100], [64, 296]] ------------------------------ Epoch 299 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.280095 - Iter 028 / 029, Loss: 0.637355 * Train accuracy / confusion: 80.60% / [[259, 103], [77, 489]], * Val accuracy / confusion: 73.39% / [[141, 89], [68, 292]] ------------------------------ Epoch 300 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.430937 - Iter 028 / 029, Loss: 0.428486 * Train accuracy / confusion: 81.25% / [[264, 99], [75, 490]], * Val accuracy / confusion: 71.86% / [[154, 76], [90, 270]] ------------------------------ Epoch 301 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.637306 - Iter 028 / 029, Loss: 0.369103 * Train accuracy / confusion: 82.22% / [[268, 96], [69, 495]], * Val accuracy / confusion: 72.20% / [[124, 106], [58, 302]] ------------------------------ Epoch 302 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.266371 - Iter 028 / 029, Loss: 0.426550 * Train accuracy / confusion: 80.06% / [[253, 108], [77, 490]], * Val accuracy / confusion: 72.20% / [[133, 97], [67, 293]] ------------------------------ Epoch 303 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.454039 - Iter 028 / 029, Loss: 0.296226 * Train accuracy / confusion: 80.39% / [[256, 106], [76, 490]], * Val accuracy / confusion: 71.36% / [[143, 87], [82, 278]] ------------------------------ Epoch 304 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.356179 - Iter 028 / 029, Loss: 0.463378 * Train accuracy / confusion: 82.44% / [[267, 96], [67, 498]], * Val accuracy / confusion: 70.34% / [[115, 115], [60, 300]] ------------------------------ Epoch 305 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.519738 - Iter 028 / 029, Loss: 0.447904 * Train accuracy / confusion: 81.14% / [[261, 104], [71, 492]], * Val accuracy / confusion: 73.90% / [[139, 91], [63, 297]] ------------------------------ Epoch 306 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.577517 - Iter 028 / 029, Loss: 0.302761 * Train accuracy / confusion: 80.71% / [[260, 104], [75, 489]], * Val accuracy / confusion: 72.88% / [[148, 82], [78, 282]] ------------------------------ Epoch 307 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.303099 - Iter 028 / 029, Loss: 0.565464 * Train accuracy / confusion: 82.76% / [[270, 90], [70, 498]], * Val accuracy / confusion: 74.41% / [[145, 85], [66, 294]] ------------------------------ Epoch 308 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.407052 - Iter 028 / 029, Loss: 0.443802 * Train accuracy / confusion: 82.33% / [[264, 96], [68, 500]], * Val accuracy / confusion: 71.36% / [[139, 91], [78, 282]] ------------------------------ Epoch 309 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.332421 - Iter 028 / 029, Loss: 0.525962 * Train accuracy / confusion: 81.25% / [[258, 102], [72, 496]], * Val accuracy / confusion: 73.73% / [[138, 92], [63, 297]] ------------------------------ Epoch 310 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.845273 - Iter 028 / 029, Loss: 0.571436 * Train accuracy / confusion: 79.74% / [[251, 109], [79, 489]], * Val accuracy / confusion: 75.42% / [[157, 73], [72, 288]] ------------------------------ Epoch 311 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.403424 - Iter 028 / 029, Loss: 0.408397 * Train accuracy / confusion: 80.39% / [[262, 102], [80, 484]], * Val accuracy / confusion: 74.07% / [[152, 78], [75, 285]] ------------------------------ Epoch 312 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.464480 - Iter 028 / 029, Loss: 0.577525 * Train accuracy / confusion: 81.47% / [[263, 97], [75, 493]], * Val accuracy / confusion: 72.03% / [[132, 98], [67, 293]] ------------------------------ Epoch 313 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.361056 - Iter 028 / 029, Loss: 0.523566 * Train accuracy / confusion: 81.90% / [[267, 98], [70, 493]], * Val accuracy / confusion: 72.71% / [[134, 96], [65, 295]] ------------------------------ Epoch 314 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.400985 - Iter 028 / 029, Loss: 0.410789 * Train accuracy / confusion: 81.25% / [[264, 102], [72, 490]], * Val accuracy / confusion: 74.58% / [[154, 76], [74, 286]] ------------------------------ Epoch 315 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.467222 - Iter 028 / 029, Loss: 0.565537 * Train accuracy / confusion: 81.25% / [[264, 97], [77, 490]], * Val accuracy / confusion: 72.20% / [[144, 86], [78, 282]] ------------------------------ Epoch 316 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.371523 - Iter 028 / 029, Loss: 0.402516 * Train accuracy / confusion: 82.11% / [[269, 96], [70, 493]], * Val accuracy / confusion: 72.71% / [[128, 102], [59, 301]] ------------------------------ Epoch 317 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.391885 - Iter 028 / 029, Loss: 0.252122 * Train accuracy / confusion: 81.68% / [[270, 95], [75, 488]], * Val accuracy / confusion: 70.85% / [[122, 108], [64, 296]] ------------------------------ Epoch 318 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.388932 - Iter 028 / 029, Loss: 0.273977 * Train accuracy / confusion: 81.14% / [[262, 100], [75, 491]], * Val accuracy / confusion: 74.75% / [[153, 77], [72, 288]] ------------------------------ Epoch 319 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.455936 - Iter 028 / 029, Loss: 0.515860 * Train accuracy / confusion: 80.71% / [[255, 106], [73, 494]], * Val accuracy / confusion: 72.03% / [[130, 100], [65, 295]] ------------------------------ Epoch 320 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.240240 - Iter 028 / 029, Loss: 0.296741 * Train accuracy / confusion: 82.65% / [[267, 96], [65, 500]], * Val accuracy / confusion: 73.73% / [[145, 85], [70, 290]] ------------------------------ Epoch 321 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.437574 - Iter 028 / 029, Loss: 0.266109 * Train accuracy / confusion: 81.14% / [[256, 103], [72, 497]], * Val accuracy / confusion: 74.41% / [[146, 84], [67, 293]] ------------------------------ Epoch 322 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.683775 - Iter 028 / 029, Loss: 0.427831 * Train accuracy / confusion: 79.09% / [[246, 116], [78, 488]], * Val accuracy / confusion: 72.37% / [[143, 87], [76, 284]] ------------------------------ Epoch 323 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.482812 - Iter 028 / 029, Loss: 0.546033 * Train accuracy / confusion: 82.00% / [[263, 100], [67, 498]], * Val accuracy / confusion: 73.90% / [[130, 100], [54, 306]] ------------------------------ Epoch 324 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.501839 - Iter 028 / 029, Loss: 0.460664 * Train accuracy / confusion: 82.76% / [[265, 98], [62, 503]], * Val accuracy / confusion: 73.22% / [[145, 85], [73, 287]] ------------------------------ Epoch 325 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.516066 - Iter 028 / 029, Loss: 0.428397 * Train accuracy / confusion: 82.22% / [[269, 94], [71, 494]], * Val accuracy / confusion: 75.08% / [[146, 84], [63, 297]] ------------------------------ Epoch 326 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.519671 - Iter 028 / 029, Loss: 0.283041 * Train accuracy / confusion: 81.57% / [[253, 103], [68, 504]], * Val accuracy / confusion: 72.20% / [[126, 104], [60, 300]] ------------------------------ Epoch 327 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.349742 - Iter 028 / 029, Loss: 0.500449 * Train accuracy / confusion: 82.11% / [[261, 102], [64, 501]], * Val accuracy / confusion: 73.22% / [[138, 92], [66, 294]] ------------------------------ Epoch 328 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.302171 - Iter 028 / 029, Loss: 0.434067 * Train accuracy / confusion: 81.25% / [[263, 95], [79, 491]], * Val accuracy / confusion: 70.85% / [[148, 82], [90, 270]] ------------------------------ Epoch 329 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.454405 - Iter 028 / 029, Loss: 0.519526 * Train accuracy / confusion: 81.03% / [[259, 100], [76, 493]], * Val accuracy / confusion: 72.71% / [[147, 83], [78, 282]] ------------------------------ Epoch 330 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.427374 - Iter 028 / 029, Loss: 0.359207 * Train accuracy / confusion: 81.25% / [[250, 109], [65, 504]], * Val accuracy / confusion: 73.05% / [[117, 113], [46, 314]] ------------------------------ Epoch 331 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.360373 - Iter 028 / 029, Loss: 0.477678 * Train accuracy / confusion: 82.87% / [[269, 95], [64, 500]], * Val accuracy / confusion: 73.90% / [[145, 85], [69, 291]] ------------------------------ Epoch 332 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.435144 - Iter 028 / 029, Loss: 0.443523 * Train accuracy / confusion: 82.11% / [[255, 101], [65, 507]], * Val accuracy / confusion: 71.86% / [[135, 95], [71, 289]] ------------------------------ Epoch 333 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.344558 - Iter 028 / 029, Loss: 0.467451 * Train accuracy / confusion: 82.11% / [[265, 100], [66, 497]], * Val accuracy / confusion: 69.66% / [[126, 104], [75, 285]] ------------------------------ Epoch 334 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.354117 - Iter 028 / 029, Loss: 0.479572 * Train accuracy / confusion: 80.71% / [[254, 105], [74, 495]], * Val accuracy / confusion: 75.08% / [[142, 88], [59, 301]] ------------------------------ Epoch 335 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.372707 - Iter 028 / 029, Loss: 0.449140 * Train accuracy / confusion: 80.50% / [[261, 99], [82, 486]], * Val accuracy / confusion: 73.73% / [[139, 91], [64, 296]] ------------------------------ Epoch 336 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.318779 - Iter 028 / 029, Loss: 0.403799 * Train accuracy / confusion: 81.79% / [[258, 109], [60, 501]], * Val accuracy / confusion: 71.69% / [[138, 92], [75, 285]] ------------------------------ Epoch 337 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.321273 - Iter 028 / 029, Loss: 0.513840 * Train accuracy / confusion: 79.63% / [[249, 113], [76, 490]], * Val accuracy / confusion: 73.39% / [[135, 95], [62, 298]] ------------------------------ Epoch 338 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.411957 - Iter 028 / 029, Loss: 0.337696 * Train accuracy / confusion: 80.60% / [[251, 111], [69, 497]], * Val accuracy / confusion: 73.05% / [[128, 102], [57, 303]] ------------------------------ Epoch 339 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.362433 - Iter 028 / 029, Loss: 0.280099 * Train accuracy / confusion: 83.73% / [[272, 89], [62, 505]], * Val accuracy / confusion: 73.73% / [[145, 85], [70, 290]] ------------------------------ Epoch 340 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.422103 - Iter 028 / 029, Loss: 0.575858 * Train accuracy / confusion: 81.36% / [[265, 97], [76, 490]], * Val accuracy / confusion: 71.86% / [[130, 100], [66, 294]] ------------------------------ Epoch 341 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.382880 - Iter 028 / 029, Loss: 0.407819 * Train accuracy / confusion: 81.79% / [[257, 105], [64, 502]], * Val accuracy / confusion: 71.02% / [[134, 96], [75, 285]] ------------------------------ Epoch 342 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.358402 - Iter 028 / 029, Loss: 0.416697 * Train accuracy / confusion: 82.00% / [[265, 97], [70, 496]], * Val accuracy / confusion: 75.08% / [[142, 88], [59, 301]] ------------------------------ Epoch 343 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.492997 - Iter 028 / 029, Loss: 0.479158 * Train accuracy / confusion: 81.03% / [[254, 103], [73, 498]], * Val accuracy / confusion: 70.68% / [[138, 92], [81, 279]] ------------------------------ Epoch 344 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.636233 - Iter 028 / 029, Loss: 0.410347 * Train accuracy / confusion: 81.79% / [[259, 101], [68, 500]], * Val accuracy / confusion: 72.37% / [[121, 109], [54, 306]] ------------------------------ Epoch 345 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.544294 - Iter 028 / 029, Loss: 0.487014 * Train accuracy / confusion: 81.57% / [[264, 99], [72, 493]], * Val accuracy / confusion: 72.20% / [[127, 103], [61, 299]] ------------------------------ Epoch 346 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.428352 - Iter 028 / 029, Loss: 0.552984 * Train accuracy / confusion: 80.50% / [[253, 113], [68, 494]], * Val accuracy / confusion: 70.34% / [[138, 92], [83, 277]] ------------------------------ Epoch 347 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.335964 - Iter 028 / 029, Loss: 0.265250 * Train accuracy / confusion: 81.25% / [[256, 107], [67, 498]], * Val accuracy / confusion: 73.56% / [[144, 86], [70, 290]] ------------------------------ Epoch 348 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.434473 - Iter 028 / 029, Loss: 0.435927 * Train accuracy / confusion: 81.36% / [[258, 102], [71, 497]], * Val accuracy / confusion: 73.90% / [[144, 86], [68, 292]] ------------------------------ Epoch 349 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.282493 - Iter 028 / 029, Loss: 0.324278 * Train accuracy / confusion: 81.03% / [[255, 109], [67, 497]], * Val accuracy / confusion: 72.54% / [[125, 105], [57, 303]] ------------------------------ Epoch 350 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.244242 - Iter 028 / 029, Loss: 0.445761 * Train accuracy / confusion: 81.47% / [[259, 103], [69, 497]], * Val accuracy / confusion: 72.71% / [[137, 93], [68, 292]] ------------------------------ Epoch 351 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.269682 - Iter 028 / 029, Loss: 0.379758 * Train accuracy / confusion: 81.57% / [[266, 99], [72, 491]], * Val accuracy / confusion: 73.90% / [[142, 88], [66, 294]] ------------------------------ Epoch 352 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.247774 - Iter 028 / 029, Loss: 0.307892 * Train accuracy / confusion: 81.14% / [[261, 103], [72, 492]], * Val accuracy / confusion: 72.88% / [[142, 88], [72, 288]] ------------------------------ Epoch 353 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.442331 - Iter 028 / 029, Loss: 0.256469 * Train accuracy / confusion: 81.03% / [[261, 101], [75, 491]], * Val accuracy / confusion: 72.20% / [[147, 83], [81, 279]] ------------------------------ Epoch 354 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.556814 - Iter 028 / 029, Loss: 0.277774 * Train accuracy / confusion: 81.90% / [[265, 96], [72, 495]], * Val accuracy / confusion: 72.71% / [[129, 101], [60, 300]] ------------------------------ Epoch 355 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.214637 - Iter 028 / 029, Loss: 0.486333 * Train accuracy / confusion: 82.11% / [[264, 98], [68, 498]], * Val accuracy / confusion: 74.58% / [[151, 79], [71, 289]] ------------------------------ Epoch 356 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.590416 - Iter 028 / 029, Loss: 0.366883 * Train accuracy / confusion: 82.65% / [[261, 97], [64, 506]], * Val accuracy / confusion: 73.56% / [[135, 95], [61, 299]] ------------------------------ Epoch 357 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.395113 - Iter 028 / 029, Loss: 0.309485 * Train accuracy / confusion: 81.68% / [[266, 97], [73, 492]], * Val accuracy / confusion: 73.56% / [[145, 85], [71, 289]] ------------------------------ Epoch 358 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.347010 - Iter 028 / 029, Loss: 0.332888 * Train accuracy / confusion: 82.11% / [[263, 100], [66, 499]], * Val accuracy / confusion: 72.20% / [[126, 104], [60, 300]] ------------------------------ Epoch 359 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.291474 - Iter 028 / 029, Loss: 0.472672 * Train accuracy / confusion: 81.14% / [[261, 105], [70, 492]], * Val accuracy / confusion: 71.69% / [[137, 93], [74, 286]] ------------------------------ Epoch 360 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.314287 - Iter 028 / 029, Loss: 0.397021 * Train accuracy / confusion: 83.08% / [[273, 91], [66, 498]], * Val accuracy / confusion: 72.54% / [[119, 111], [51, 309]] ------------------------------ Epoch 361 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.344737 - Iter 028 / 029, Loss: 0.423284 * Train accuracy / confusion: 80.60% / [[254, 104], [76, 494]], * Val accuracy / confusion: 71.86% / [[141, 89], [77, 283]] ------------------------------ Epoch 362 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.575588 - Iter 028 / 029, Loss: 0.410089 * Train accuracy / confusion: 81.03% / [[259, 103], [73, 493]], * Val accuracy / confusion: 70.68% / [[146, 84], [89, 271]] ------------------------------ Epoch 363 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.565509 - Iter 028 / 029, Loss: 0.422469 * Train accuracy / confusion: 81.03% / [[260, 107], [69, 492]], * Val accuracy / confusion: 74.24% / [[151, 79], [73, 287]] ------------------------------ Epoch 364 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.299474 - Iter 028 / 029, Loss: 0.369447 * Train accuracy / confusion: 80.39% / [[255, 108], [74, 491]], * Val accuracy / confusion: 72.71% / [[128, 102], [59, 301]] ------------------------------ Epoch 365 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.529390 - Iter 028 / 029, Loss: 0.296582 * Train accuracy / confusion: 81.79% / [[267, 96], [73, 492]], * Val accuracy / confusion: 72.88% / [[140, 90], [70, 290]] ------------------------------ Epoch 366 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.239761 - Iter 028 / 029, Loss: 0.351598 * Train accuracy / confusion: 81.03% / [[262, 99], [77, 490]], * Val accuracy / confusion: 73.39% / [[139, 91], [66, 294]] ------------------------------ Epoch 367 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.418054 - Iter 028 / 029, Loss: 0.345788 * Train accuracy / confusion: 81.57% / [[258, 104], [67, 499]], * Val accuracy / confusion: 73.90% / [[142, 88], [66, 294]] ------------------------------ Epoch 368 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.348856 - Iter 028 / 029, Loss: 0.294819 * Train accuracy / confusion: 82.00% / [[257, 103], [64, 504]], * Val accuracy / confusion: 71.86% / [[129, 101], [65, 295]] ------------------------------ Epoch 369 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.329408 - Iter 028 / 029, Loss: 0.400508 * Train accuracy / confusion: 82.11% / [[255, 107], [59, 507]], * Val accuracy / confusion: 73.90% / [[134, 96], [58, 302]] ------------------------------ Epoch 370 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.433856 - Iter 028 / 029, Loss: 0.406458 * Train accuracy / confusion: 82.11% / [[260, 104], [62, 502]], * Val accuracy / confusion: 75.25% / [[137, 93], [53, 307]] ------------------------------ Epoch 371 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.382700 - Iter 028 / 029, Loss: 0.353008 * Train accuracy / confusion: 80.71% / [[254, 107], [72, 495]], * Val accuracy / confusion: 72.37% / [[130, 100], [63, 297]] ------------------------------ Epoch 372 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.498722 - Iter 028 / 029, Loss: 0.484345 * Train accuracy / confusion: 79.74% / [[248, 114], [74, 492]], * Val accuracy / confusion: 74.07% / [[139, 91], [62, 298]] ------------------------------ Epoch 373 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.452542 - Iter 028 / 029, Loss: 0.463277 * Train accuracy / confusion: 83.19% / [[266, 100], [56, 506]], * Val accuracy / confusion: 73.90% / [[150, 80], [74, 286]] ------------------------------ Epoch 374 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.448078 - Iter 028 / 029, Loss: 0.289718 * Train accuracy / confusion: 82.97% / [[274, 91], [67, 496]], * Val accuracy / confusion: 73.05% / [[144, 86], [73, 287]] ------------------------------ Epoch 375 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.260672 - Iter 028 / 029, Loss: 0.350046 * Train accuracy / confusion: 81.57% / [[253, 108], [63, 504]], * Val accuracy / confusion: 72.20% / [[123, 107], [57, 303]] ------------------------------ Epoch 376 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.569342 - Iter 028 / 029, Loss: 0.495123 * Train accuracy / confusion: 79.09% / [[247, 113], [81, 487]], * Val accuracy / confusion: 72.37% / [[126, 104], [59, 301]] ------------------------------ Epoch 377 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.406905 - Iter 028 / 029, Loss: 0.383160 * Train accuracy / confusion: 82.11% / [[264, 98], [68, 498]], * Val accuracy / confusion: 73.22% / [[142, 88], [70, 290]] ------------------------------ Epoch 378 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.302654 - Iter 028 / 029, Loss: 0.422823 * Train accuracy / confusion: 83.73% / [[263, 98], [53, 514]], * Val accuracy / confusion: 73.90% / [[134, 96], [58, 302]] ------------------------------ Epoch 379 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.426390 - Iter 028 / 029, Loss: 0.324113 * Train accuracy / confusion: 81.68% / [[257, 102], [68, 501]], * Val accuracy / confusion: 72.71% / [[131, 99], [62, 298]] ------------------------------ Epoch 380 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.437760 - Iter 028 / 029, Loss: 0.258664 * Train accuracy / confusion: 81.90% / [[256, 106], [62, 504]], * Val accuracy / confusion: 73.22% / [[143, 87], [71, 289]] ------------------------------ Epoch 381 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.439087 - Iter 028 / 029, Loss: 0.423668 * Train accuracy / confusion: 82.97% / [[273, 90], [68, 497]], * Val accuracy / confusion: 74.92% / [[129, 101], [47, 313]] ------------------------------ Epoch 382 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.425236 - Iter 028 / 029, Loss: 0.289222 * Train accuracy / confusion: 82.97% / [[269, 96], [62, 501]], * Val accuracy / confusion: 73.73% / [[129, 101], [54, 306]] ------------------------------ Epoch 383 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.357248 - Iter 028 / 029, Loss: 0.264046 * Train accuracy / confusion: 80.93% / [[260, 106], [71, 491]], * Val accuracy / confusion: 72.37% / [[136, 94], [69, 291]] ------------------------------ Epoch 384 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.377271 - Iter 028 / 029, Loss: 0.482548 * Train accuracy / confusion: 80.82% / [[259, 106], [72, 491]], * Val accuracy / confusion: 76.10% / [[150, 80], [61, 299]] ------------------------------ Epoch 385 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.348376 - Iter 028 / 029, Loss: 0.645275 * Train accuracy / confusion: 81.03% / [[262, 94], [82, 490]], * Val accuracy / confusion: 72.37% / [[141, 89], [74, 286]] ------------------------------ Epoch 386 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.319788 - Iter 028 / 029, Loss: 0.446662 * Train accuracy / confusion: 82.00% / [[266, 94], [73, 495]], * Val accuracy / confusion: 72.54% / [[146, 84], [78, 282]] ------------------------------ Epoch 387 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.426928 - Iter 028 / 029, Loss: 0.407937 * Train accuracy / confusion: 81.68% / [[263, 101], [69, 495]], * Val accuracy / confusion: 72.37% / [[140, 90], [73, 287]] ------------------------------ Epoch 388 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.396897 - Iter 028 / 029, Loss: 0.492409 * Train accuracy / confusion: 82.54% / [[264, 96], [66, 502]], * Val accuracy / confusion: 74.07% / [[134, 96], [57, 303]] ------------------------------ Epoch 389 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.380194 - Iter 028 / 029, Loss: 0.478947 * Train accuracy / confusion: 81.68% / [[262, 102], [68, 496]], * Val accuracy / confusion: 72.20% / [[131, 99], [65, 295]] ------------------------------ Epoch 390 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.259582 - Iter 028 / 029, Loss: 0.434206 * Train accuracy / confusion: 81.68% / [[268, 95], [75, 490]], * Val accuracy / confusion: 72.37% / [[136, 94], [69, 291]] ------------------------------ Epoch 391 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.515442 - Iter 028 / 029, Loss: 0.464316 * Train accuracy / confusion: 82.87% / [[269, 91], [68, 500]], * Val accuracy / confusion: 73.90% / [[140, 90], [64, 296]] ------------------------------ Epoch 392 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.387395 - Iter 028 / 029, Loss: 0.498621 * Train accuracy / confusion: 82.00% / [[272, 92], [75, 489]], * Val accuracy / confusion: 72.88% / [[136, 94], [66, 294]] ------------------------------ Epoch 393 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.382962 - Iter 028 / 029, Loss: 0.338390 * Train accuracy / confusion: 82.97% / [[265, 96], [62, 505]], * Val accuracy / confusion: 75.25% / [[157, 73], [73, 287]] ------------------------------ Epoch 394 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.296068 - Iter 028 / 029, Loss: 0.363602 * Train accuracy / confusion: 81.47% / [[257, 106], [66, 499]], * Val accuracy / confusion: 74.07% / [[144, 86], [67, 293]] ------------------------------ Epoch 395 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.371624 - Iter 028 / 029, Loss: 0.591197 * Train accuracy / confusion: 81.25% / [[257, 104], [70, 497]], * Val accuracy / confusion: 73.39% / [[139, 91], [66, 294]] ------------------------------ Epoch 396 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.499198 - Iter 028 / 029, Loss: 0.477228 * Train accuracy / confusion: 80.71% / [[251, 114], [65, 498]], * Val accuracy / confusion: 71.86% / [[138, 92], [74, 286]] ------------------------------ Epoch 397 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.295174 - Iter 028 / 029, Loss: 0.518862 * Train accuracy / confusion: 80.82% / [[258, 102], [76, 492]], * Val accuracy / confusion: 73.05% / [[145, 85], [74, 286]] ------------------------------ Epoch 398 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.462105 - Iter 028 / 029, Loss: 0.396340 * Train accuracy / confusion: 82.33% / [[270, 92], [72, 494]], * Val accuracy / confusion: 71.69% / [[128, 102], [65, 295]] ------------------------------ Epoch 399 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.418152 - Iter 028 / 029, Loss: 0.440232 * Train accuracy / confusion: 82.33% / [[269, 97], [67, 495]], * Val accuracy / confusion: 72.88% / [[149, 81], [79, 281]] ------------------------------ Epoch 400 / 500, Learning rate: 2.75e-04 ------------------------------ - Iter 014 / 029, Loss: 0.282839 - Iter 028 / 029, Loss: 0.347396 * Train accuracy / confusion: 82.97% / [[274, 89], [69, 496]], * Val accuracy / confusion: 72.88% / [[138, 92], [68, 292]] ------------------------------ Epoch 401 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.345942 - Iter 028 / 029, Loss: 0.535641 * Train accuracy / confusion: 80.39% / [[263, 97], [85, 483]], * Val accuracy / confusion: 72.54% / [[136, 94], [68, 292]] ------------------------------ Epoch 402 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.543060 - Iter 028 / 029, Loss: 0.246822 * Train accuracy / confusion: 80.82% / [[255, 103], [75, 495]], * Val accuracy / confusion: 74.75% / [[149, 81], [68, 292]] ------------------------------ Epoch 403 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.430310 - Iter 028 / 029, Loss: 0.325491 * Train accuracy / confusion: 82.00% / [[266, 96], [71, 495]], * Val accuracy / confusion: 72.20% / [[143, 87], [77, 283]] ------------------------------ Epoch 404 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.293748 - Iter 028 / 029, Loss: 0.384209 * Train accuracy / confusion: 81.25% / [[262, 97], [77, 492]], * Val accuracy / confusion: 73.90% / [[144, 86], [68, 292]] ------------------------------ Epoch 405 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.378335 - Iter 028 / 029, Loss: 0.373132 * Train accuracy / confusion: 81.79% / [[262, 98], [71, 497]], * Val accuracy / confusion: 72.03% / [[140, 90], [75, 285]] ------------------------------ Epoch 406 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.558456 - Iter 028 / 029, Loss: 0.590828 * Train accuracy / confusion: 81.57% / [[265, 97], [74, 492]], * Val accuracy / confusion: 73.73% / [[145, 85], [70, 290]] ------------------------------ Epoch 407 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.293674 - Iter 028 / 029, Loss: 0.348781 * Train accuracy / confusion: 82.33% / [[265, 98], [66, 499]], * Val accuracy / confusion: 72.20% / [[138, 92], [72, 288]] ------------------------------ Epoch 408 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.610203 - Iter 028 / 029, Loss: 0.397057 * Train accuracy / confusion: 82.97% / [[261, 100], [58, 509]], * Val accuracy / confusion: 73.90% / [[140, 90], [64, 296]] ------------------------------ Epoch 409 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.362008 - Iter 028 / 029, Loss: 0.418117 * Train accuracy / confusion: 81.90% / [[261, 102], [66, 499]], * Val accuracy / confusion: 72.03% / [[134, 96], [69, 291]] ------------------------------ Epoch 410 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.411345 - Iter 028 / 029, Loss: 0.648985 * Train accuracy / confusion: 82.54% / [[261, 100], [62, 505]], * Val accuracy / confusion: 73.39% / [[145, 85], [72, 288]] ------------------------------ Epoch 411 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.540097 - Iter 028 / 029, Loss: 0.523966 * Train accuracy / confusion: 81.57% / [[263, 98], [73, 494]], * Val accuracy / confusion: 70.51% / [[143, 87], [87, 273]] ------------------------------ Epoch 412 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.388189 - Iter 028 / 029, Loss: 0.416926 * Train accuracy / confusion: 82.11% / [[263, 100], [66, 499]], * Val accuracy / confusion: 72.54% / [[139, 91], [71, 289]] ------------------------------ Epoch 413 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.369335 - Iter 028 / 029, Loss: 0.303548 * Train accuracy / confusion: 83.19% / [[269, 94], [62, 503]], * Val accuracy / confusion: 75.25% / [[146, 84], [62, 298]] ------------------------------ Epoch 414 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.288236 - Iter 028 / 029, Loss: 0.371806 * Train accuracy / confusion: 81.47% / [[264, 100], [72, 492]], * Val accuracy / confusion: 74.92% / [[144, 86], [62, 298]] ------------------------------ Epoch 415 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.437463 - Iter 028 / 029, Loss: 0.308299 * Train accuracy / confusion: 81.68% / [[267, 93], [77, 491]], * Val accuracy / confusion: 71.36% / [[138, 92], [77, 283]] ------------------------------ Epoch 416 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.470270 - Iter 028 / 029, Loss: 0.384361 * Train accuracy / confusion: 82.65% / [[268, 93], [68, 499]], * Val accuracy / confusion: 73.56% / [[140, 90], [66, 294]] ------------------------------ Epoch 417 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.376243 - Iter 028 / 029, Loss: 0.432118 * Train accuracy / confusion: 82.33% / [[263, 100], [64, 501]], * Val accuracy / confusion: 74.92% / [[152, 78], [70, 290]] ------------------------------ Epoch 418 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.524779 - Iter 028 / 029, Loss: 0.503572 * Train accuracy / confusion: 81.79% / [[273, 92], [77, 486]], * Val accuracy / confusion: 74.92% / [[140, 90], [58, 302]] ------------------------------ Epoch 419 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.326729 - Iter 028 / 029, Loss: 0.319463 * Train accuracy / confusion: 80.39% / [[253, 109], [73, 493]], * Val accuracy / confusion: 72.88% / [[137, 93], [67, 293]] ------------------------------ Epoch 420 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.314350 - Iter 028 / 029, Loss: 0.232259 * Train accuracy / confusion: 81.57% / [[263, 97], [74, 494]], * Val accuracy / confusion: 74.07% / [[146, 84], [69, 291]] ------------------------------ Epoch 421 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.295432 - Iter 028 / 029, Loss: 0.433015 * Train accuracy / confusion: 82.54% / [[264, 98], [64, 502]], * Val accuracy / confusion: 72.54% / [[143, 87], [75, 285]] ------------------------------ Epoch 422 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.405420 - Iter 028 / 029, Loss: 0.302466 * Train accuracy / confusion: 82.00% / [[266, 101], [66, 495]], * Val accuracy / confusion: 72.20% / [[143, 87], [77, 283]] ------------------------------ Epoch 423 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.453487 - Iter 028 / 029, Loss: 0.462958 * Train accuracy / confusion: 82.97% / [[270, 90], [68, 500]], * Val accuracy / confusion: 71.53% / [[141, 89], [79, 281]] ------------------------------ Epoch 424 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.409293 - Iter 028 / 029, Loss: 0.330438 * Train accuracy / confusion: 82.33% / [[267, 99], [65, 497]], * Val accuracy / confusion: 75.59% / [[144, 86], [58, 302]] ------------------------------ Epoch 425 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.344037 - Iter 028 / 029, Loss: 0.406725 * Train accuracy / confusion: 82.65% / [[266, 99], [62, 501]], * Val accuracy / confusion: 74.75% / [[138, 92], [57, 303]] ------------------------------ Epoch 426 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.422073 - Iter 028 / 029, Loss: 0.569520 * Train accuracy / confusion: 83.41% / [[272, 89], [65, 502]], * Val accuracy / confusion: 73.90% / [[147, 83], [71, 289]] ------------------------------ Epoch 427 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.416923 - Iter 028 / 029, Loss: 0.212020 * Train accuracy / confusion: 82.00% / [[266, 90], [77, 495]], * Val accuracy / confusion: 71.69% / [[142, 88], [79, 281]] ------------------------------ Epoch 428 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.371224 - Iter 028 / 029, Loss: 0.303846 * Train accuracy / confusion: 83.08% / [[268, 96], [61, 503]], * Val accuracy / confusion: 74.07% / [[147, 83], [70, 290]] ------------------------------ Epoch 429 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.328609 - Iter 028 / 029, Loss: 0.554522 * Train accuracy / confusion: 80.60% / [[258, 104], [76, 490]], * Val accuracy / confusion: 74.58% / [[141, 89], [61, 299]] ------------------------------ Epoch 430 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.431328 - Iter 028 / 029, Loss: 0.435530 * Train accuracy / confusion: 83.08% / [[265, 96], [61, 506]], * Val accuracy / confusion: 71.36% / [[140, 90], [79, 281]] ------------------------------ Epoch 431 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.452750 - Iter 028 / 029, Loss: 0.335324 * Train accuracy / confusion: 82.33% / [[260, 100], [64, 504]], * Val accuracy / confusion: 71.36% / [[126, 104], [65, 295]] ------------------------------ Epoch 432 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.364207 - Iter 028 / 029, Loss: 0.442222 * Train accuracy / confusion: 82.65% / [[267, 97], [64, 500]], * Val accuracy / confusion: 72.37% / [[137, 93], [70, 290]] ------------------------------ Epoch 433 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.352609 - Iter 028 / 029, Loss: 0.380674 * Train accuracy / confusion: 82.11% / [[263, 100], [66, 499]], * Val accuracy / confusion: 74.24% / [[142, 88], [64, 296]] ------------------------------ Epoch 434 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.567965 - Iter 028 / 029, Loss: 0.346423 * Train accuracy / confusion: 81.03% / [[258, 106], [70, 494]], * Val accuracy / confusion: 73.56% / [[138, 92], [64, 296]] ------------------------------ Epoch 435 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.411434 - Iter 028 / 029, Loss: 0.340151 * Train accuracy / confusion: 82.00% / [[256, 104], [63, 505]], * Val accuracy / confusion: 74.24% / [[148, 82], [70, 290]] ------------------------------ Epoch 436 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.362837 - Iter 028 / 029, Loss: 0.329406 * Train accuracy / confusion: 82.54% / [[264, 98], [64, 502]], * Val accuracy / confusion: 73.22% / [[144, 86], [72, 288]] ------------------------------ Epoch 437 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.354696 - Iter 028 / 029, Loss: 0.413233 * Train accuracy / confusion: 82.22% / [[266, 99], [66, 497]], * Val accuracy / confusion: 73.39% / [[135, 95], [62, 298]] ------------------------------ Epoch 438 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.365816 - Iter 028 / 029, Loss: 0.290742 * Train accuracy / confusion: 82.44% / [[261, 100], [63, 504]], * Val accuracy / confusion: 73.39% / [[144, 86], [71, 289]] ------------------------------ Epoch 439 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.297706 - Iter 028 / 029, Loss: 0.483229 * Train accuracy / confusion: 83.41% / [[265, 96], [58, 509]], * Val accuracy / confusion: 70.68% / [[126, 104], [69, 291]] ------------------------------ Epoch 440 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.272313 - Iter 028 / 029, Loss: 0.487117 * Train accuracy / confusion: 82.87% / [[268, 97], [62, 501]], * Val accuracy / confusion: 71.19% / [[134, 96], [74, 286]] ------------------------------ Epoch 441 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.416476 - Iter 028 / 029, Loss: 0.401602 * Train accuracy / confusion: 82.54% / [[266, 96], [66, 500]], * Val accuracy / confusion: 72.54% / [[133, 97], [65, 295]] ------------------------------ Epoch 442 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.443110 - Iter 028 / 029, Loss: 0.401612 * Train accuracy / confusion: 82.87% / [[263, 99], [60, 506]], * Val accuracy / confusion: 72.54% / [[133, 97], [65, 295]] ------------------------------ Epoch 443 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.382329 - Iter 028 / 029, Loss: 0.236970 * Train accuracy / confusion: 82.00% / [[264, 100], [67, 497]], * Val accuracy / confusion: 71.36% / [[132, 98], [71, 289]] ------------------------------ Epoch 444 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.376342 - Iter 028 / 029, Loss: 0.392211 * Train accuracy / confusion: 82.00% / [[263, 101], [66, 498]], * Val accuracy / confusion: 71.53% / [[141, 89], [79, 281]] ------------------------------ Epoch 445 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.349500 - Iter 028 / 029, Loss: 0.253842 * Train accuracy / confusion: 81.79% / [[259, 103], [66, 500]], * Val accuracy / confusion: 72.54% / [[141, 89], [73, 287]] ------------------------------ Epoch 446 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.251506 - Iter 028 / 029, Loss: 0.321744 * Train accuracy / confusion: 83.73% / [[270, 92], [59, 507]], * Val accuracy / confusion: 73.56% / [[145, 85], [71, 289]] ------------------------------ Epoch 447 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.432763 - Iter 028 / 029, Loss: 0.372333 * Train accuracy / confusion: 82.44% / [[266, 97], [66, 499]], * Val accuracy / confusion: 73.05% / [[139, 91], [68, 292]] ------------------------------ Epoch 448 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.328596 - Iter 028 / 029, Loss: 0.335799 * Train accuracy / confusion: 82.11% / [[267, 96], [70, 495]], * Val accuracy / confusion: 73.39% / [[152, 78], [79, 281]] ------------------------------ Epoch 449 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.257205 - Iter 028 / 029, Loss: 0.487441 * Train accuracy / confusion: 82.22% / [[258, 103], [62, 505]], * Val accuracy / confusion: 73.56% / [[135, 95], [61, 299]] ------------------------------ Epoch 450 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.444047 - Iter 028 / 029, Loss: 0.383278 * Train accuracy / confusion: 81.90% / [[261, 98], [70, 499]], * Val accuracy / confusion: 72.54% / [[140, 90], [72, 288]] ------------------------------ Epoch 451 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.397259 - Iter 028 / 029, Loss: 0.339583 * Train accuracy / confusion: 83.41% / [[268, 91], [63, 506]], * Val accuracy / confusion: 73.90% / [[137, 93], [61, 299]] ------------------------------ Epoch 452 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.555565 - Iter 028 / 029, Loss: 0.442423 * Train accuracy / confusion: 81.47% / [[264, 95], [77, 492]], * Val accuracy / confusion: 72.71% / [[135, 95], [66, 294]] ------------------------------ Epoch 453 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.467307 - Iter 028 / 029, Loss: 0.380258 * Train accuracy / confusion: 79.96% / [[253, 114], [72, 489]], * Val accuracy / confusion: 74.58% / [[137, 93], [57, 303]] ------------------------------ Epoch 454 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.455848 - Iter 028 / 029, Loss: 0.444122 * Train accuracy / confusion: 82.65% / [[273, 93], [68, 494]], * Val accuracy / confusion: 74.07% / [[144, 86], [67, 293]] ------------------------------ Epoch 455 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.434213 - Iter 028 / 029, Loss: 0.252419 * Train accuracy / confusion: 82.65% / [[267, 98], [63, 500]], * Val accuracy / confusion: 75.08% / [[146, 84], [63, 297]] ------------------------------ Epoch 456 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.479068 - Iter 028 / 029, Loss: 0.545041 * Train accuracy / confusion: 83.41% / [[272, 89], [65, 502]], * Val accuracy / confusion: 73.39% / [[147, 83], [74, 286]] ------------------------------ Epoch 457 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.343753 - Iter 028 / 029, Loss: 0.388393 * Train accuracy / confusion: 81.79% / [[263, 99], [70, 496]], * Val accuracy / confusion: 70.85% / [[133, 97], [75, 285]] ------------------------------ Epoch 458 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.312434 - Iter 028 / 029, Loss: 0.481189 * Train accuracy / confusion: 81.03% / [[258, 101], [75, 494]], * Val accuracy / confusion: 73.39% / [[139, 91], [66, 294]] ------------------------------ Epoch 459 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.379725 - Iter 028 / 029, Loss: 0.315577 * Train accuracy / confusion: 81.79% / [[264, 101], [68, 495]], * Val accuracy / confusion: 72.20% / [[132, 98], [66, 294]] ------------------------------ Epoch 460 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.361602 - Iter 028 / 029, Loss: 0.558350 * Train accuracy / confusion: 82.11% / [[266, 97], [69, 496]], * Val accuracy / confusion: 70.51% / [[132, 98], [76, 284]] ------------------------------ Epoch 461 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.414665 - Iter 028 / 029, Loss: 0.409231 * Train accuracy / confusion: 82.97% / [[262, 100], [58, 508]], * Val accuracy / confusion: 72.88% / [[140, 90], [70, 290]] ------------------------------ Epoch 462 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.305465 - Iter 028 / 029, Loss: 0.271523 * Train accuracy / confusion: 81.57% / [[266, 98], [73, 491]], * Val accuracy / confusion: 72.20% / [[127, 103], [61, 299]] ------------------------------ Epoch 463 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.436162 - Iter 028 / 029, Loss: 0.275824 * Train accuracy / confusion: 83.19% / [[267, 92], [64, 505]], * Val accuracy / confusion: 74.07% / [[138, 92], [61, 299]] ------------------------------ Epoch 464 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.495344 - Iter 028 / 029, Loss: 0.326480 * Train accuracy / confusion: 83.51% / [[265, 95], [58, 510]], * Val accuracy / confusion: 70.68% / [[124, 106], [67, 293]] ------------------------------ Epoch 465 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.589354 - Iter 028 / 029, Loss: 0.323719 * Train accuracy / confusion: 81.47% / [[261, 98], [74, 495]], * Val accuracy / confusion: 74.41% / [[155, 75], [76, 284]] ------------------------------ Epoch 466 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.435321 - Iter 028 / 029, Loss: 0.345872 * Train accuracy / confusion: 82.11% / [[264, 101], [65, 498]], * Val accuracy / confusion: 72.37% / [[130, 100], [63, 297]] ------------------------------ Epoch 467 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.556424 - Iter 028 / 029, Loss: 0.563280 * Train accuracy / confusion: 82.33% / [[262, 102], [62, 502]], * Val accuracy / confusion: 73.22% / [[136, 94], [64, 296]] ------------------------------ Epoch 468 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.336377 - Iter 028 / 029, Loss: 0.332509 * Train accuracy / confusion: 82.54% / [[261, 100], [62, 505]], * Val accuracy / confusion: 70.68% / [[130, 100], [73, 287]] ------------------------------ Epoch 469 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.369090 - Iter 028 / 029, Loss: 0.339190 * Train accuracy / confusion: 82.97% / [[272, 91], [67, 498]], * Val accuracy / confusion: 72.71% / [[135, 95], [66, 294]] ------------------------------ Epoch 470 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.501346 - Iter 028 / 029, Loss: 0.454081 * Train accuracy / confusion: 81.68% / [[261, 100], [70, 497]], * Val accuracy / confusion: 70.51% / [[136, 94], [80, 280]] ------------------------------ Epoch 471 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.372219 - Iter 028 / 029, Loss: 0.436720 * Train accuracy / confusion: 82.33% / [[261, 99], [65, 503]], * Val accuracy / confusion: 70.85% / [[140, 90], [82, 278]] ------------------------------ Epoch 472 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.502718 - Iter 028 / 029, Loss: 0.489460 * Train accuracy / confusion: 81.57% / [[263, 101], [70, 494]], * Val accuracy / confusion: 74.24% / [[143, 87], [65, 295]] ------------------------------ Epoch 473 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.318247 - Iter 028 / 029, Loss: 0.412750 * Train accuracy / confusion: 82.76% / [[268, 92], [68, 500]], * Val accuracy / confusion: 73.56% / [[142, 88], [68, 292]] ------------------------------ Epoch 474 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.331596 - Iter 028 / 029, Loss: 0.442325 * Train accuracy / confusion: 81.90% / [[268, 96], [72, 492]], * Val accuracy / confusion: 74.75% / [[144, 86], [63, 297]] ------------------------------ Epoch 475 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.399215 - Iter 028 / 029, Loss: 0.468462 * Train accuracy / confusion: 82.44% / [[264, 96], [67, 501]], * Val accuracy / confusion: 74.07% / [[141, 89], [64, 296]] ------------------------------ Epoch 476 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.320731 - Iter 028 / 029, Loss: 0.488063 * Train accuracy / confusion: 82.11% / [[267, 95], [71, 495]], * Val accuracy / confusion: 72.20% / [[135, 95], [69, 291]] ------------------------------ Epoch 477 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.307512 - Iter 028 / 029, Loss: 0.386056 * Train accuracy / confusion: 81.90% / [[257, 106], [62, 503]], * Val accuracy / confusion: 74.07% / [[139, 91], [62, 298]] ------------------------------ Epoch 478 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.351812 - Iter 028 / 029, Loss: 0.285818 * Train accuracy / confusion: 81.57% / [[256, 106], [65, 501]], * Val accuracy / confusion: 72.54% / [[138, 92], [70, 290]] ------------------------------ Epoch 479 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.493167 - Iter 028 / 029, Loss: 0.634601 * Train accuracy / confusion: 82.76% / [[262, 101], [59, 506]], * Val accuracy / confusion: 72.20% / [[133, 97], [67, 293]] ------------------------------ Epoch 480 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.531314 - Iter 028 / 029, Loss: 0.344306 * Train accuracy / confusion: 83.41% / [[267, 96], [58, 507]], * Val accuracy / confusion: 71.53% / [[140, 90], [78, 282]] ------------------------------ Epoch 481 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.339256 - Iter 028 / 029, Loss: 0.423119 * Train accuracy / confusion: 83.84% / [[267, 94], [56, 511]], * Val accuracy / confusion: 72.03% / [[139, 91], [74, 286]] ------------------------------ Epoch 482 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.405294 - Iter 028 / 029, Loss: 0.428652 * Train accuracy / confusion: 82.65% / [[265, 95], [66, 502]], * Val accuracy / confusion: 73.56% / [[139, 91], [65, 295]] ------------------------------ Epoch 483 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.249633 - Iter 028 / 029, Loss: 0.466315 * Train accuracy / confusion: 84.38% / [[270, 90], [55, 513]], * Val accuracy / confusion: 72.37% / [[137, 93], [70, 290]] ------------------------------ Epoch 484 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.402961 - Iter 028 / 029, Loss: 0.428418 * Train accuracy / confusion: 85.13% / [[277, 84], [54, 513]], * Val accuracy / confusion: 73.73% / [[138, 92], [63, 297]] ------------------------------ Epoch 485 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.406913 - Iter 028 / 029, Loss: 0.328121 * Train accuracy / confusion: 83.94% / [[273, 93], [56, 506]], * Val accuracy / confusion: 71.53% / [[129, 101], [67, 293]] ------------------------------ Epoch 486 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.347313 - Iter 028 / 029, Loss: 0.402374 * Train accuracy / confusion: 82.11% / [[267, 100], [66, 495]], * Val accuracy / confusion: 71.19% / [[137, 93], [77, 283]] ------------------------------ Epoch 487 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.401665 - Iter 028 / 029, Loss: 0.305311 * Train accuracy / confusion: 81.36% / [[256, 103], [70, 499]], * Val accuracy / confusion: 71.53% / [[134, 96], [72, 288]] ------------------------------ Epoch 488 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.370284 - Iter 028 / 029, Loss: 0.303399 * Train accuracy / confusion: 81.47% / [[258, 99], [73, 498]], * Val accuracy / confusion: 71.36% / [[138, 92], [77, 283]] ------------------------------ Epoch 489 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.292115 - Iter 028 / 029, Loss: 0.360909 * Train accuracy / confusion: 82.76% / [[265, 95], [65, 503]], * Val accuracy / confusion: 74.58% / [[138, 92], [58, 302]] ------------------------------ Epoch 490 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.288336 - Iter 028 / 029, Loss: 0.457211 * Train accuracy / confusion: 83.51% / [[276, 82], [71, 499]], * Val accuracy / confusion: 72.88% / [[137, 93], [67, 293]] ------------------------------ Epoch 491 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.321181 - Iter 028 / 029, Loss: 0.622468 * Train accuracy / confusion: 82.22% / [[265, 94], [71, 498]], * Val accuracy / confusion: 73.22% / [[140, 90], [68, 292]] ------------------------------ Epoch 492 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.309405 - Iter 028 / 029, Loss: 0.238427 * Train accuracy / confusion: 84.27% / [[275, 89], [57, 507]], * Val accuracy / confusion: 74.75% / [[150, 80], [69, 291]] ------------------------------ Epoch 493 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.435387 - Iter 028 / 029, Loss: 0.259644 * Train accuracy / confusion: 83.19% / [[266, 96], [60, 506]], * Val accuracy / confusion: 71.86% / [[135, 95], [71, 289]] ------------------------------ Epoch 494 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.365335 - Iter 028 / 029, Loss: 0.266054 * Train accuracy / confusion: 83.19% / [[266, 94], [62, 506]], * Val accuracy / confusion: 71.69% / [[127, 103], [64, 296]] ------------------------------ Epoch 495 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.437100 - Iter 028 / 029, Loss: 0.288437 * Train accuracy / confusion: 83.51% / [[270, 93], [60, 505]], * Val accuracy / confusion: 70.68% / [[127, 103], [70, 290]] ------------------------------ Epoch 496 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.441537 - Iter 028 / 029, Loss: 0.448774 * Train accuracy / confusion: 83.51% / [[267, 95], [58, 508]], * Val accuracy / confusion: 71.69% / [[127, 103], [64, 296]] ------------------------------ Epoch 497 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.433623 - Iter 028 / 029, Loss: 0.216329 * Train accuracy / confusion: 82.44% / [[265, 97], [66, 500]], * Val accuracy / confusion: 73.05% / [[135, 95], [64, 296]] ------------------------------ Epoch 498 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.573803 - Iter 028 / 029, Loss: 0.383795 * Train accuracy / confusion: 83.08% / [[260, 101], [56, 511]], * Val accuracy / confusion: 71.36% / [[118, 112], [57, 303]] ------------------------------ Epoch 499 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.314825 - Iter 028 / 029, Loss: 0.328990 * Train accuracy / confusion: 81.57% / [[258, 102], [69, 499]], * Val accuracy / confusion: 71.69% / [[132, 98], [69, 291]] ------------------------------ Epoch 500 / 500, Learning rate: 2.75e-05 ------------------------------ - Iter 014 / 029, Loss: 0.455984 - Iter 028 / 029, Loss: 0.519702 * Train accuracy / confusion: 82.33% / [[264, 100], [64, 500]], * Val accuracy / confusion: 73.22% / [[137, 93], [65, 295]] **************************************** Training Ends ****************************************
- Test accuracy (last model): 73.06% - Confusion matrix (last model): [[ 893 517] [ 453 1737]]
- Test accuracy (best model): 71.00% - Confusion matrix (best model): [[ 767 643] [ 401 1789]]
# checkpoint save path
if save_checkpoint:
os.makedirs('checkpoint/', exist_ok=True)
today = datetime.date.today()
torch.save(best_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_ResNet_best')
torch.save(last_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_ResNet_last')
print('- Debug table:')
pprint.pp(last_test_debug, indent=2, width=100)
- Debug table:
{ '01183': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01303198_020317'},
'00697': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00983533_290618'},
'00825': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01129445_130220'},
'00504': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00813343_041218'},
'00192': {'GT': 0, 'Acc': ' 6.67%', 'Pred': [2, 28], 'edfname': '00608961_131118'},
'00134': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00446328_171116'},
'00741': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '01025734_280715'},
'00206': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00616193_090218'},
'01231': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01334787_211117'},
'00793': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01086373_020615'},
'01045': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01235281_191015'},
'00407': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '00740694_110315'},
'00669': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '00957862_230317'},
'00843': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01135545_230715'},
'00029': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00164098_180919'},
'00299': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00671212_160819'},
'00702': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00985987_180518'},
'01069': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01243158_301115'},
'00913': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01151967_160414'},
'01307': {'GT': 0, 'Acc': ' 3.33%', 'Pred': [1, 29], 'edfname': '01376302_060718'},
'00638': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00941649_111218'},
'00286': {'GT': 1, 'Acc': ' 13.33%', 'Pred': [26, 4], 'edfname': '00663561_030414'},
'00954': {'GT': 1, 'Acc': ' 33.33%', 'Pred': [20, 10], 'edfname': '01178797_240914'},
'00587': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00894185_250817'},
'00542': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '00852650_170818'},
'00996': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '01204692_120315'},
'00403': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00739162_011215'},
'00408': {'GT': 0, 'Acc': ' 10.00%', 'Pred': [3, 27], 'edfname': '00740750_110315'},
'00078': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00324958_271118'},
'00277': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00657017_281218'},
'00671': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00958455_200917'},
'01066': {'GT': 0, 'Acc': ' 63.33%', 'Pred': [19, 11], 'edfname': '01242983_071215'},
'00965': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01186214'},
'01125': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '01276737_300616'},
'00227': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00626957_071217'},
'00531': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '00840844_250119'},
'00088': {'GT': 1, 'Acc': ' 46.67%', 'Pred': [16, 14], 'edfname': '00344923_021116'},
'00267': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '00650465_160318'},
'00069': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '00307906_230617'},
'00365': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00712852_060418'},
'00991': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01203444_090819'},
'00815': {'GT': 0, 'Acc': ' 70.00%', 'Pred': [21, 9], 'edfname': '01125477_030918'},
'01351': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01409497_111219'},
'00065': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00293228_070918'},
'00952': {'GT': 1, 'Acc': ' 66.67%', 'Pred': [10, 20], 'edfname': '01178672_300518'},
'00124': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '00418981_060116'},
'00854': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01138301_230114'},
'00472': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00784418_201016'},
'01258': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01348039_181017'},
'01375': {'GT': 1, 'Acc': ' 53.33%', 'Pred': [14, 16], 'edfname': '01429374_230519'},
'00885': {'GT': 0, 'Acc': ' 23.33%', 'Pred': [7, 23], 'edfname': '01142810_180214'},
'00917': {'GT': 0, 'Acc': ' 16.67%', 'Pred': [5, 25], 'edfname': '01154159_230414'},
'00938': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '01161826_050916'},
'00881': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01141790_190214'},
'00096': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '00369252_131216'},
'01075': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01250004_260116'},
'01165': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '01296533_281116'},
'01067': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01242984_211215'},
'00828': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01131959_310118'},
'01337': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01400560_160419'},
'00383': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00723110_240419'},
'00900': {'GT': 0, 'Acc': ' 33.33%', 'Pred': [10, 20], 'edfname': '01147100'},
'01336': {'GT': 1, 'Acc': ' 60.00%', 'Pred': [12, 18], 'edfname': '01398060_050918'},
'01115': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01271298_270319'},
'00667': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00956561_241116'},
'00439': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '00760780_141118'},
'00369': {'GT': 1, 'Acc': ' 33.33%', 'Pred': [20, 10], 'edfname': '00715828_111016'},
'00955': {'GT': 1, 'Acc': ' 80.00%', 'Pred': [6, 24], 'edfname': '01178888_161117'},
'00300': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00671379_290617'},
'01196': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01307883_100217'},
'00923': {'GT': 0, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '01155730_070514'},
'00058': {'GT': 0, 'Acc': ' 23.33%', 'Pred': [7, 23], 'edfname': '00285244_020414'},
'00584': {'GT': 1, 'Acc': ' 30.00%', 'Pred': [21, 9], 'edfname': '00891889_060717'},
'00749': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01027623_260916'},
'01334': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01396872_021018'},
'00588': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00895530_090616'},
'00679': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00963069_150618'},
'00385': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00723232_270318'},
'00018': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00128526_180817'},
'01281': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01358607_280918'},
'00651': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00951808_251116'},
'01253': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01344212_240817'},
'01035': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01231654_260417'},
'00551': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '00865039_170816'},
'00870': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01139947_120214'},
'00578': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00888613_080618'},
'00730': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01011922_270815'},
'00516': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00823206_130514'},
'01330': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '01392885_240718'},
'00944': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01168853_070316'},
'00125': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '00418981_090316'},
'00508': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00817022_010415'},
'01317': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01381606_160518'},
'00608': {'GT': 1, 'Acc': ' 3.33%', 'Pred': [29, 1], 'edfname': '00907971_030217'},
'00471': {'GT': 1, 'Acc': ' 76.67%', 'Pred': [7, 23], 'edfname': '00784417_100315'},
'00821': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01128393_300715'},
'00122': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00416942_190516'},
'01007': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01211467_070415'},
'01247': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01339759_310717'},
'00173': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00601028_290618'},
'01026': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '01225123_050815'},
'01018': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01216443_240518'},
'00418': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00745209_220916'},
'01206': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01314786_200317'},
'01215': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01321744_130417'},
'01105': {'GT': 0, 'Acc': ' 13.33%', 'Pred': [4, 26], 'edfname': '01266696_110516'},
'00598': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '00899964_110414'},
'00851': {'GT': 0, 'Acc': ' 26.67%', 'Pred': [8, 22], 'edfname': '01138297_230114'},
'01138': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '01281605_070716'},
'00079': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00325929_170119'},
'00245': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00637371_050917'},
'00591': {'GT': 0, 'Acc': ' 70.00%', 'Pred': [21, 9], 'edfname': '00896386_240914'},
'00329': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '00685248_150414'},
'00272': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00651389_281016'},
'00176': {'GT': 0, 'Acc': ' 73.33%', 'Pred': [22, 8], 'edfname': '00602435_270217'},
'00807': {'GT': 1, 'Acc': ' 23.33%', 'Pred': [23, 7], 'edfname': '01112291_231115'},
'00271': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00651252_140618'},
'00712': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00988278_210915'},
'00974': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01193508_171214'},
'01163': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01296342_141116'}}
model = ResNet(block=BasicResBlock, conv_layers=[1, 1, 1, 1], n_fc=3,
n_input=train_dataset[0]['signal'].shape[0], n_output=2, n_start=64,
kernel_size=9, use_age=False)
model = model.to(device, dtype=torch.float32)
print(model)
print()
n = count_parameters(model)
print(f'The Number of parameters of the model: {n:,}')
ResNet(
(input_stage): Sequential(
(0): Conv1d(20, 64, kernel_size=(27,), stride=(2,), padding=(13,), bias=False)
(1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(2): ReLU()
)
(conv_stage1): Sequential(
(0): BasicResBlock(
(conv1): Conv1d(64, 64, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(64, 64, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(conv_stage2): Sequential(
(0): BasicResBlock(
(conv1): Conv1d(64, 128, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(128, 128, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(64, 128, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(conv_stage3): Sequential(
(0): BasicResBlock(
(conv1): Conv1d(128, 256, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(256, 256, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(128, 256, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(conv_stage4): Sequential(
(0): BasicResBlock(
(conv1): Conv1d(256, 512, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(512, 512, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(256, 512, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(final_pool): AdaptiveAvgPool1d(output_size=1)
(fc_stage): Sequential(
(0): Sequential(
(0): Linear(in_features=512, out_features=256, bias=False)
(1): Dropout(p=0.1, inplace=False)
(2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU()
)
(1): Sequential(
(0): Linear(in_features=256, out_features=128, bias=False)
(1): Dropout(p=0.1, inplace=False)
(2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU()
)
(2): Sequential(
(0): Linear(in_features=128, out_features=64, bias=False)
(1): Dropout(p=0.1, inplace=False)
(2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU()
)
(3): Linear(in_features=64, out_features=2, bias=True)
)
)
The Number of parameters of the model: 5,104,002
record = learning_rate_search(model,
min_log_lr=-4.5,
max_log_lr=-1.4,
trials=300,
epochs=1)
draw_learning_rate_record(record)
best_log_lr = record[np.argmax(np.array([v for lr, v in record]))][0]
# best_log_lr = -2.3
print('best_log_lr:', best_log_lr)
best_log_lr: -3.827056599863147
# reduce the learning after [lr_schedule_step] epochs by a factor of 10
n_epoch = 500
lr_schedule_step = 200
log_interval = len(train_loader) // 2
loss_history = []
train_acc_history = []
val_acc_history = []
best_val_acc = 0
model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=10 ** best_log_lr, weight_decay=0.0001)
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=lr_schedule_step, gamma=0.1)
print(f'{"*"*40} Training Starts {"*"*40}')
for epoch in tqdm(range(1, n_epoch + 1)):
print(f'{"-"*30} Epoch {epoch:03d} / {n_epoch:03d}, Learning rate: {optimizer.param_groups[-1]["lr"]:.2e} {"-"*30}')
# train
loss, train_accuracy, train_confusion = train_one_epoch(model, optimizer, log_interval)
loss_history.extend(loss)
train_acc_history.append(train_accuracy)
# validation
val_accuracy, val_confusion = check_val_accuracy(model, repeat=5)
val_acc_history.append(val_accuracy)
if best_val_acc < val_accuracy:
best_val_acc = val_accuracy
best_model_state = deepcopy(model.state_dict())
# learning rate schedule
scheduler.step()
print()
print(f'* Train accuracy / confusion: {train_accuracy:.2f}% / {train_confusion.tolist()}, ')
print(f'* Val accuracy / confusion: {val_accuracy:.2f}% / {val_confusion.tolist()}')
print()
print(f'{"*"*40} Training Ends {"*"*40}')
# draw the training loss plot
draw_loss_plot(loss_history)
draw_accuracy_history(train_acc_history, val_acc_history)
# test the last model
last_model_state = deepcopy(model.state_dict())
last_test_accuracy, last_test_confusion, last_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (last model): {last_test_accuracy:.2f}%')
print('- Confusion matrix (last model):\n', last_test_confusion)
print()
draw_confusion(last_test_confusion)
# test the best model
model.load_state_dict(best_model_state)
best_test_accuracy, best_test_confusion, best_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (best model): {best_test_accuracy:.2f}%')
print('- Confusion matrix (best model):\n', best_test_confusion)
print()
draw_confusion(best_test_confusion)
**************************************** Training Starts ****************************************
------------------------------ Epoch 001 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.698186 - Iter 028 / 029, Loss: 0.687529 * Train accuracy / confusion: 54.20% / [[198, 164], [261, 305]], * Val accuracy / confusion: 53.56% / [[155, 75], [199, 161]] ------------------------------ Epoch 002 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.715212 - Iter 028 / 029, Loss: 0.628814 * Train accuracy / confusion: 60.13% / [[201, 157], [213, 357]], * Val accuracy / confusion: 63.39% / [[85, 145], [71, 289]] ------------------------------ Epoch 003 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.523305 - Iter 028 / 029, Loss: 0.640459 * Train accuracy / confusion: 67.24% / [[198, 164], [140, 426]], * Val accuracy / confusion: 60.68% / [[179, 51], [181, 179]] ------------------------------ Epoch 004 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.618545 - Iter 028 / 029, Loss: 0.659770 * Train accuracy / confusion: 66.38% / [[189, 174], [138, 427]], * Val accuracy / confusion: 58.31% / [[88, 142], [104, 256]] ------------------------------ Epoch 005 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.674361 - Iter 028 / 029, Loss: 0.597958 * Train accuracy / confusion: 65.09% / [[187, 177], [147, 417]], * Val accuracy / confusion: 61.86% / [[57, 173], [52, 308]] ------------------------------ Epoch 006 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.619505 - Iter 028 / 029, Loss: 0.642829 * Train accuracy / confusion: 67.89% / [[186, 177], [121, 444]], * Val accuracy / confusion: 59.32% / [[39, 191], [49, 311]] ------------------------------ Epoch 007 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.529335 - Iter 028 / 029, Loss: 0.519776 * Train accuracy / confusion: 69.07% / [[182, 183], [104, 459]], * Val accuracy / confusion: 64.07% / [[72, 158], [54, 306]] ------------------------------ Epoch 008 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.642090 - Iter 028 / 029, Loss: 0.510653 * Train accuracy / confusion: 69.72% / [[182, 180], [101, 465]], * Val accuracy / confusion: 64.92% / [[151, 79], [128, 232]] ------------------------------ Epoch 009 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.470005 - Iter 028 / 029, Loss: 0.733318 * Train accuracy / confusion: 70.37% / [[195, 167], [108, 458]], * Val accuracy / confusion: 66.44% / [[117, 113], [85, 275]] ------------------------------ Epoch 010 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.599118 - Iter 028 / 029, Loss: 0.618784 * Train accuracy / confusion: 71.44% / [[202, 158], [107, 461]], * Val accuracy / confusion: 62.37% / [[84, 146], [76, 284]] ------------------------------ Epoch 011 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.558975 - Iter 028 / 029, Loss: 0.601361 * Train accuracy / confusion: 69.29% / [[179, 183], [102, 464]], * Val accuracy / confusion: 65.08% / [[57, 173], [33, 327]] ------------------------------ Epoch 012 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.504687 - Iter 028 / 029, Loss: 0.491317 * Train accuracy / confusion: 70.37% / [[189, 168], [107, 464]], * Val accuracy / confusion: 64.07% / [[59, 171], [41, 319]] ------------------------------ Epoch 013 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.500799 - Iter 028 / 029, Loss: 0.554301 * Train accuracy / confusion: 70.80% / [[208, 152], [119, 449]], * Val accuracy / confusion: 65.25% / [[65, 165], [40, 320]] ------------------------------ Epoch 014 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.430042 - Iter 028 / 029, Loss: 0.738192 * Train accuracy / confusion: 73.28% / [[204, 159], [89, 476]], * Val accuracy / confusion: 62.20% / [[80, 150], [73, 287]] ------------------------------ Epoch 015 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.590494 - Iter 028 / 029, Loss: 0.522257 * Train accuracy / confusion: 71.55% / [[202, 160], [104, 462]], * Val accuracy / confusion: 63.90% / [[99, 131], [82, 278]] ------------------------------ Epoch 016 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.512249 - Iter 028 / 029, Loss: 0.577792 * Train accuracy / confusion: 70.91% / [[189, 174], [96, 469]], * Val accuracy / confusion: 65.08% / [[82, 148], [58, 302]] ------------------------------ Epoch 017 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.498022 - Iter 028 / 029, Loss: 0.556439 * Train accuracy / confusion: 73.81% / [[216, 143], [100, 469]], * Val accuracy / confusion: 63.73% / [[182, 48], [166, 194]] ------------------------------ Epoch 018 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.463858 - Iter 028 / 029, Loss: 0.571341 * Train accuracy / confusion: 72.84% / [[208, 155], [97, 468]], * Val accuracy / confusion: 67.46% / [[87, 143], [49, 311]] ------------------------------ Epoch 019 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.643432 - Iter 028 / 029, Loss: 0.581060 * Train accuracy / confusion: 75.11% / [[223, 138], [93, 474]], * Val accuracy / confusion: 65.76% / [[129, 101], [101, 259]] ------------------------------ Epoch 020 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.505615 - Iter 028 / 029, Loss: 0.485989 * Train accuracy / confusion: 73.92% / [[220, 141], [101, 466]], * Val accuracy / confusion: 65.25% / [[156, 74], [131, 229]] ------------------------------ Epoch 021 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.505145 - Iter 028 / 029, Loss: 0.510340 * Train accuracy / confusion: 74.78% / [[231, 128], [106, 463]], * Val accuracy / confusion: 64.58% / [[65, 165], [44, 316]] ------------------------------ Epoch 022 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.610881 - Iter 028 / 029, Loss: 0.580444 * Train accuracy / confusion: 71.88% / [[203, 157], [104, 464]], * Val accuracy / confusion: 67.12% / [[106, 124], [70, 290]] ------------------------------ Epoch 023 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.351076 - Iter 028 / 029, Loss: 0.545875 * Train accuracy / confusion: 75.65% / [[238, 124], [102, 464]], * Val accuracy / confusion: 54.58% / [[210, 20], [248, 112]] ------------------------------ Epoch 024 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.544713 - Iter 028 / 029, Loss: 0.514779 * Train accuracy / confusion: 75.32% / [[230, 131], [98, 469]], * Val accuracy / confusion: 64.58% / [[158, 72], [137, 223]] ------------------------------ Epoch 025 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.507225 - Iter 028 / 029, Loss: 0.551431 * Train accuracy / confusion: 74.68% / [[221, 142], [93, 472]], * Val accuracy / confusion: 66.95% / [[172, 58], [137, 223]] ------------------------------ Epoch 026 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.350024 - Iter 028 / 029, Loss: 0.454487 * Train accuracy / confusion: 76.62% / [[235, 128], [89, 476]], * Val accuracy / confusion: 61.69% / [[172, 58], [168, 192]] ------------------------------ Epoch 027 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.779407 - Iter 028 / 029, Loss: 0.486255 * Train accuracy / confusion: 73.71% / [[226, 135], [109, 458]], * Val accuracy / confusion: 63.90% / [[82, 148], [65, 295]] ------------------------------ Epoch 028 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.459585 - Iter 028 / 029, Loss: 0.557428 * Train accuracy / confusion: 73.92% / [[227, 132], [110, 459]], * Val accuracy / confusion: 67.12% / [[79, 151], [43, 317]] ------------------------------ Epoch 029 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.624794 - Iter 028 / 029, Loss: 0.463639 * Train accuracy / confusion: 75.54% / [[234, 129], [98, 467]], * Val accuracy / confusion: 67.63% / [[166, 64], [127, 233]] ------------------------------ Epoch 030 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.621245 - Iter 028 / 029, Loss: 0.407795 * Train accuracy / confusion: 76.51% / [[229, 132], [86, 481]], * Val accuracy / confusion: 68.64% / [[106, 124], [61, 299]] ------------------------------ Epoch 031 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.633444 - Iter 028 / 029, Loss: 0.524132 * Train accuracy / confusion: 76.29% / [[228, 132], [88, 480]], * Val accuracy / confusion: 64.75% / [[59, 171], [37, 323]] ------------------------------ Epoch 032 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.501906 - Iter 028 / 029, Loss: 0.336359 * Train accuracy / confusion: 78.02% / [[248, 115], [89, 476]], * Val accuracy / confusion: 68.98% / [[94, 136], [47, 313]] ------------------------------ Epoch 033 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.446459 - Iter 028 / 029, Loss: 0.408054 * Train accuracy / confusion: 77.37% / [[251, 110], [100, 467]], * Val accuracy / confusion: 68.81% / [[118, 112], [72, 288]] ------------------------------ Epoch 034 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.683058 - Iter 028 / 029, Loss: 0.661599 * Train accuracy / confusion: 74.68% / [[224, 139], [96, 469]], * Val accuracy / confusion: 67.63% / [[169, 61], [130, 230]] ------------------------------ Epoch 035 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.417362 - Iter 028 / 029, Loss: 0.508198 * Train accuracy / confusion: 77.37% / [[231, 127], [83, 487]], * Val accuracy / confusion: 67.63% / [[170, 60], [131, 229]] ------------------------------ Epoch 036 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.282501 - Iter 028 / 029, Loss: 0.533660 * Train accuracy / confusion: 76.40% / [[225, 135], [84, 484]], * Val accuracy / confusion: 66.61% / [[113, 117], [80, 280]] ------------------------------ Epoch 037 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.607086 - Iter 028 / 029, Loss: 0.602925 * Train accuracy / confusion: 74.46% / [[235, 127], [110, 456]], * Val accuracy / confusion: 63.90% / [[194, 36], [177, 183]] ------------------------------ Epoch 038 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.456161 - Iter 028 / 029, Loss: 0.395122 * Train accuracy / confusion: 76.19% / [[229, 132], [89, 478]], * Val accuracy / confusion: 67.12% / [[184, 46], [148, 212]] ------------------------------ Epoch 039 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.304781 - Iter 028 / 029, Loss: 0.583587 * Train accuracy / confusion: 76.19% / [[236, 128], [93, 471]], * Val accuracy / confusion: 66.61% / [[71, 159], [38, 322]] ------------------------------ Epoch 040 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.367455 - Iter 028 / 029, Loss: 0.493807 * Train accuracy / confusion: 76.72% / [[237, 122], [94, 475]], * Val accuracy / confusion: 68.81% / [[99, 131], [53, 307]] ------------------------------ Epoch 041 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.515872 - Iter 028 / 029, Loss: 0.452325 * Train accuracy / confusion: 78.02% / [[243, 119], [85, 481]], * Val accuracy / confusion: 62.71% / [[206, 24], [196, 164]] ------------------------------ Epoch 042 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.393204 - Iter 028 / 029, Loss: 0.529149 * Train accuracy / confusion: 76.72% / [[231, 128], [88, 481]], * Val accuracy / confusion: 69.32% / [[161, 69], [112, 248]] ------------------------------ Epoch 043 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.405889 - Iter 028 / 029, Loss: 0.521403 * Train accuracy / confusion: 76.40% / [[240, 121], [98, 469]], * Val accuracy / confusion: 67.46% / [[69, 161], [31, 329]] ------------------------------ Epoch 044 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.603530 - Iter 028 / 029, Loss: 0.554418 * Train accuracy / confusion: 77.48% / [[263, 103], [106, 456]], * Val accuracy / confusion: 68.47% / [[181, 49], [137, 223]] ------------------------------ Epoch 045 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.670914 - Iter 028 / 029, Loss: 0.626721 * Train accuracy / confusion: 78.66% / [[252, 111], [87, 478]], * Val accuracy / confusion: 69.49% / [[128, 102], [78, 282]] ------------------------------ Epoch 046 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.633382 - Iter 028 / 029, Loss: 0.537839 * Train accuracy / confusion: 77.05% / [[231, 132], [81, 484]], * Val accuracy / confusion: 66.61% / [[63, 167], [30, 330]] ------------------------------ Epoch 047 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.510166 - Iter 028 / 029, Loss: 0.517480 * Train accuracy / confusion: 79.53% / [[258, 103], [87, 480]], * Val accuracy / confusion: 64.24% / [[153, 77], [134, 226]] ------------------------------ Epoch 048 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.441441 - Iter 028 / 029, Loss: 0.430894 * Train accuracy / confusion: 78.77% / [[253, 111], [86, 478]], * Val accuracy / confusion: 67.80% / [[149, 81], [109, 251]] ------------------------------ Epoch 049 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.515578 - Iter 028 / 029, Loss: 0.351507 * Train accuracy / confusion: 78.34% / [[257, 100], [101, 470]], * Val accuracy / confusion: 62.88% / [[130, 100], [119, 241]] ------------------------------ Epoch 050 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.527958 - Iter 028 / 029, Loss: 0.421661 * Train accuracy / confusion: 77.48% / [[256, 103], [106, 463]], * Val accuracy / confusion: 63.22% / [[27, 203], [14, 346]] ------------------------------ Epoch 051 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.417858 - Iter 028 / 029, Loss: 0.522573 * Train accuracy / confusion: 76.72% / [[239, 122], [94, 473]], * Val accuracy / confusion: 67.80% / [[104, 126], [64, 296]] ------------------------------ Epoch 052 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.482788 - Iter 028 / 029, Loss: 0.515221 * Train accuracy / confusion: 79.74% / [[257, 103], [85, 483]], * Val accuracy / confusion: 64.92% / [[69, 161], [46, 314]] ------------------------------ Epoch 053 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.539064 - Iter 028 / 029, Loss: 0.397071 * Train accuracy / confusion: 79.63% / [[246, 119], [70, 493]], * Val accuracy / confusion: 61.19% / [[4, 226], [3, 357]] ------------------------------ Epoch 054 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.356146 - Iter 028 / 029, Loss: 0.434334 * Train accuracy / confusion: 78.88% / [[255, 108], [88, 477]], * Val accuracy / confusion: 68.81% / [[163, 67], [117, 243]] ------------------------------ Epoch 055 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.529659 - Iter 028 / 029, Loss: 0.306615 * Train accuracy / confusion: 78.12% / [[260, 100], [103, 465]], * Val accuracy / confusion: 67.46% / [[165, 65], [127, 233]] ------------------------------ Epoch 056 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.489620 - Iter 028 / 029, Loss: 0.460753 * Train accuracy / confusion: 79.74% / [[254, 111], [77, 486]], * Val accuracy / confusion: 52.37% / [[208, 22], [259, 101]] ------------------------------ Epoch 057 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.327300 - Iter 028 / 029, Loss: 0.423009 * Train accuracy / confusion: 76.19% / [[241, 123], [98, 466]], * Val accuracy / confusion: 63.22% / [[106, 124], [93, 267]] ------------------------------ Epoch 058 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.521802 - Iter 028 / 029, Loss: 0.277204 * Train accuracy / confusion: 78.23% / [[253, 106], [96, 473]], * Val accuracy / confusion: 67.63% / [[85, 145], [46, 314]] ------------------------------ Epoch 059 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.332961 - Iter 028 / 029, Loss: 0.639409 * Train accuracy / confusion: 77.59% / [[246, 118], [90, 474]], * Val accuracy / confusion: 68.98% / [[122, 108], [75, 285]] ------------------------------ Epoch 060 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.272853 - Iter 028 / 029, Loss: 0.655067 * Train accuracy / confusion: 77.05% / [[240, 121], [92, 475]], * Val accuracy / confusion: 68.14% / [[159, 71], [117, 243]] ------------------------------ Epoch 061 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.400563 - Iter 028 / 029, Loss: 0.442228 * Train accuracy / confusion: 79.09% / [[260, 104], [90, 474]], * Val accuracy / confusion: 66.78% / [[155, 75], [121, 239]] ------------------------------ Epoch 062 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.280038 - Iter 028 / 029, Loss: 0.333527 * Train accuracy / confusion: 78.99% / [[260, 108], [87, 473]], * Val accuracy / confusion: 69.15% / [[172, 58], [124, 236]] ------------------------------ Epoch 063 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.429542 - Iter 028 / 029, Loss: 0.521057 * Train accuracy / confusion: 80.28% / [[260, 104], [79, 485]], * Val accuracy / confusion: 66.27% / [[160, 70], [129, 231]] ------------------------------ Epoch 064 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.414909 - Iter 028 / 029, Loss: 0.295826 * Train accuracy / confusion: 80.50% / [[272, 89], [92, 475]], * Val accuracy / confusion: 69.32% / [[137, 93], [88, 272]] ------------------------------ Epoch 065 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.279060 - Iter 028 / 029, Loss: 0.383013 * Train accuracy / confusion: 79.31% / [[249, 113], [79, 487]], * Val accuracy / confusion: 70.00% / [[159, 71], [106, 254]] ------------------------------ Epoch 066 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.424772 - Iter 028 / 029, Loss: 0.590908 * Train accuracy / confusion: 77.69% / [[253, 110], [97, 468]], * Val accuracy / confusion: 64.24% / [[180, 50], [161, 199]] ------------------------------ Epoch 067 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.416700 - Iter 028 / 029, Loss: 0.610663 * Train accuracy / confusion: 76.83% / [[242, 116], [99, 471]], * Val accuracy / confusion: 68.98% / [[169, 61], [122, 238]] ------------------------------ Epoch 068 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.526414 - Iter 028 / 029, Loss: 0.452343 * Train accuracy / confusion: 76.72% / [[247, 115], [101, 465]], * Val accuracy / confusion: 70.34% / [[130, 100], [75, 285]] ------------------------------ Epoch 069 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.457093 - Iter 028 / 029, Loss: 0.328435 * Train accuracy / confusion: 78.66% / [[257, 107], [91, 473]], * Val accuracy / confusion: 60.85% / [[207, 23], [208, 152]] ------------------------------ Epoch 070 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.546784 - Iter 028 / 029, Loss: 0.491586 * Train accuracy / confusion: 78.34% / [[242, 120], [81, 485]], * Val accuracy / confusion: 67.63% / [[191, 39], [152, 208]] ------------------------------ Epoch 071 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.325255 - Iter 028 / 029, Loss: 0.467731 * Train accuracy / confusion: 79.74% / [[268, 96], [92, 472]], * Val accuracy / confusion: 67.97% / [[163, 67], [122, 238]] ------------------------------ Epoch 072 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.329815 - Iter 028 / 029, Loss: 0.422901 * Train accuracy / confusion: 79.53% / [[260, 105], [85, 478]], * Val accuracy / confusion: 63.56% / [[186, 44], [171, 189]] ------------------------------ Epoch 073 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.420807 - Iter 028 / 029, Loss: 0.468883 * Train accuracy / confusion: 79.20% / [[258, 104], [89, 477]], * Val accuracy / confusion: 66.78% / [[105, 125], [71, 289]] ------------------------------ Epoch 074 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.417800 - Iter 028 / 029, Loss: 0.471641 * Train accuracy / confusion: 79.63% / [[257, 106], [83, 482]], * Val accuracy / confusion: 67.12% / [[134, 96], [98, 262]] ------------------------------ Epoch 075 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.432854 - Iter 028 / 029, Loss: 0.388851 * Train accuracy / confusion: 80.60% / [[256, 104], [76, 492]], * Val accuracy / confusion: 68.81% / [[133, 97], [87, 273]] ------------------------------ Epoch 076 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.453135 - Iter 028 / 029, Loss: 0.385281 * Train accuracy / confusion: 78.45% / [[250, 114], [86, 478]], * Val accuracy / confusion: 71.36% / [[118, 112], [57, 303]] ------------------------------ Epoch 077 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.749250 - Iter 028 / 029, Loss: 0.256430 * Train accuracy / confusion: 81.36% / [[271, 93], [80, 484]], * Val accuracy / confusion: 68.81% / [[168, 62], [122, 238]] ------------------------------ Epoch 078 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.464180 - Iter 028 / 029, Loss: 0.399760 * Train accuracy / confusion: 79.96% / [[266, 93], [93, 476]], * Val accuracy / confusion: 67.80% / [[142, 88], [102, 258]] ------------------------------ Epoch 079 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.324898 - Iter 028 / 029, Loss: 0.292560 * Train accuracy / confusion: 80.39% / [[267, 93], [89, 479]], * Val accuracy / confusion: 68.14% / [[91, 139], [49, 311]] ------------------------------ Epoch 080 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.300359 - Iter 028 / 029, Loss: 0.846496 * Train accuracy / confusion: 81.25% / [[258, 106], [68, 496]], * Val accuracy / confusion: 71.02% / [[154, 76], [95, 265]] ------------------------------ Epoch 081 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.489035 - Iter 028 / 029, Loss: 0.320615 * Train accuracy / confusion: 80.60% / [[261, 104], [76, 487]], * Val accuracy / confusion: 65.93% / [[181, 49], [152, 208]] ------------------------------ Epoch 082 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.355828 - Iter 028 / 029, Loss: 0.384066 * Train accuracy / confusion: 81.47% / [[269, 91], [81, 487]], * Val accuracy / confusion: 67.12% / [[96, 134], [60, 300]] ------------------------------ Epoch 083 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.297942 - Iter 028 / 029, Loss: 0.431498 * Train accuracy / confusion: 80.28% / [[260, 102], [81, 485]], * Val accuracy / confusion: 71.36% / [[147, 83], [86, 274]] ------------------------------ Epoch 084 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.422333 - Iter 028 / 029, Loss: 0.564923 * Train accuracy / confusion: 82.11% / [[272, 91], [75, 490]], * Val accuracy / confusion: 66.10% / [[200, 30], [170, 190]] ------------------------------ Epoch 085 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.433593 - Iter 028 / 029, Loss: 0.375761 * Train accuracy / confusion: 82.11% / [[267, 98], [68, 495]], * Val accuracy / confusion: 68.98% / [[148, 82], [101, 259]] ------------------------------ Epoch 086 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.281467 - Iter 028 / 029, Loss: 0.381033 * Train accuracy / confusion: 81.47% / [[259, 101], [71, 497]], * Val accuracy / confusion: 70.17% / [[125, 105], [71, 289]] ------------------------------ Epoch 087 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.478534 - Iter 028 / 029, Loss: 0.428718 * Train accuracy / confusion: 79.85% / [[265, 99], [88, 476]], * Val accuracy / confusion: 66.61% / [[66, 164], [33, 327]] ------------------------------ Epoch 088 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.417711 - Iter 028 / 029, Loss: 0.524583 * Train accuracy / confusion: 82.00% / [[264, 98], [69, 497]], * Val accuracy / confusion: 67.46% / [[128, 102], [90, 270]] ------------------------------ Epoch 089 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.357795 - Iter 028 / 029, Loss: 0.435429 * Train accuracy / confusion: 79.53% / [[252, 109], [81, 486]], * Val accuracy / confusion: 65.08% / [[37, 193], [13, 347]] ------------------------------ Epoch 090 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.417206 - Iter 028 / 029, Loss: 0.488656 * Train accuracy / confusion: 82.22% / [[267, 96], [69, 496]], * Val accuracy / confusion: 66.44% / [[201, 29], [169, 191]] ------------------------------ Epoch 091 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.405482 - Iter 028 / 029, Loss: 0.602964 * Train accuracy / confusion: 81.14% / [[257, 103], [72, 496]], * Val accuracy / confusion: 69.32% / [[157, 73], [108, 252]] ------------------------------ Epoch 092 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.314209 - Iter 028 / 029, Loss: 0.390733 * Train accuracy / confusion: 83.84% / [[287, 77], [73, 491]], * Val accuracy / confusion: 66.78% / [[125, 105], [91, 269]] ------------------------------ Epoch 093 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.553693 - Iter 028 / 029, Loss: 0.429307 * Train accuracy / confusion: 82.33% / [[260, 100], [64, 504]], * Val accuracy / confusion: 65.76% / [[140, 90], [112, 248]] ------------------------------ Epoch 094 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.351762 - Iter 028 / 029, Loss: 0.483640 * Train accuracy / confusion: 82.87% / [[276, 85], [74, 493]], * Val accuracy / confusion: 67.12% / [[150, 80], [114, 246]] ------------------------------ Epoch 095 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.517834 - Iter 028 / 029, Loss: 0.334245 * Train accuracy / confusion: 80.50% / [[261, 99], [82, 486]], * Val accuracy / confusion: 65.76% / [[65, 165], [37, 323]] ------------------------------ Epoch 096 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.362136 - Iter 028 / 029, Loss: 0.405534 * Train accuracy / confusion: 82.11% / [[265, 97], [69, 497]], * Val accuracy / confusion: 64.58% / [[173, 57], [152, 208]] ------------------------------ Epoch 097 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.337050 - Iter 028 / 029, Loss: 0.345742 * Train accuracy / confusion: 81.57% / [[281, 80], [91, 476]], * Val accuracy / confusion: 63.73% / [[169, 61], [153, 207]] ------------------------------ Epoch 098 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.369631 - Iter 028 / 029, Loss: 0.557646 * Train accuracy / confusion: 81.79% / [[265, 98], [71, 494]], * Val accuracy / confusion: 67.12% / [[86, 144], [50, 310]] ------------------------------ Epoch 099 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.386847 - Iter 028 / 029, Loss: 0.410402 * Train accuracy / confusion: 80.71% / [[276, 89], [90, 473]], * Val accuracy / confusion: 65.08% / [[45, 185], [21, 339]] ------------------------------ Epoch 100 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.497676 - Iter 028 / 029, Loss: 0.376478 * Train accuracy / confusion: 81.03% / [[267, 93], [83, 485]], * Val accuracy / confusion: 61.36% / [[201, 29], [199, 161]] ------------------------------ Epoch 101 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.404787 - Iter 028 / 029, Loss: 0.457976 * Train accuracy / confusion: 83.30% / [[273, 91], [64, 500]], * Val accuracy / confusion: 67.97% / [[196, 34], [155, 205]] ------------------------------ Epoch 102 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.356446 - Iter 028 / 029, Loss: 0.441851 * Train accuracy / confusion: 82.54% / [[278, 86], [76, 488]], * Val accuracy / confusion: 66.78% / [[155, 75], [121, 239]] ------------------------------ Epoch 103 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.331204 - Iter 028 / 029, Loss: 0.274142 * Train accuracy / confusion: 80.71% / [[269, 94], [85, 480]], * Val accuracy / confusion: 70.34% / [[142, 88], [87, 273]] ------------------------------ Epoch 104 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.879600 - Iter 028 / 029, Loss: 0.328139 * Train accuracy / confusion: 81.25% / [[264, 99], [75, 490]], * Val accuracy / confusion: 69.66% / [[156, 74], [105, 255]] ------------------------------ Epoch 105 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.430471 - Iter 028 / 029, Loss: 0.484554 * Train accuracy / confusion: 82.44% / [[263, 96], [67, 502]], * Val accuracy / confusion: 63.39% / [[65, 165], [51, 309]] ------------------------------ Epoch 106 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.288305 - Iter 028 / 029, Loss: 0.641610 * Train accuracy / confusion: 82.11% / [[274, 92], [74, 488]], * Val accuracy / confusion: 66.61% / [[167, 63], [134, 226]] ------------------------------ Epoch 107 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.226612 - Iter 028 / 029, Loss: 0.269778 * Train accuracy / confusion: 82.33% / [[276, 90], [74, 488]], * Val accuracy / confusion: 70.68% / [[146, 84], [89, 271]] ------------------------------ Epoch 108 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.302967 - Iter 028 / 029, Loss: 0.397816 * Train accuracy / confusion: 82.65% / [[281, 82], [79, 486]], * Val accuracy / confusion: 63.90% / [[187, 43], [170, 190]] ------------------------------ Epoch 109 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.240076 - Iter 028 / 029, Loss: 0.377519 * Train accuracy / confusion: 82.11% / [[274, 90], [76, 488]], * Val accuracy / confusion: 70.34% / [[136, 94], [81, 279]] ------------------------------ Epoch 110 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.356031 - Iter 028 / 029, Loss: 0.281982 * Train accuracy / confusion: 84.38% / [[278, 86], [59, 505]], * Val accuracy / confusion: 68.47% / [[193, 37], [149, 211]] ------------------------------ Epoch 111 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.425375 - Iter 028 / 029, Loss: 0.309075 * Train accuracy / confusion: 82.22% / [[269, 91], [74, 494]], * Val accuracy / confusion: 67.97% / [[159, 71], [118, 242]] ------------------------------ Epoch 112 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.339894 - Iter 028 / 029, Loss: 0.305441 * Train accuracy / confusion: 83.08% / [[282, 78], [79, 489]], * Val accuracy / confusion: 66.78% / [[58, 172], [24, 336]] ------------------------------ Epoch 113 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.289771 - Iter 028 / 029, Loss: 0.405865 * Train accuracy / confusion: 83.73% / [[282, 80], [71, 495]], * Val accuracy / confusion: 70.51% / [[108, 122], [52, 308]] ------------------------------ Epoch 114 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.298463 - Iter 028 / 029, Loss: 0.351230 * Train accuracy / confusion: 82.65% / [[275, 84], [77, 492]], * Val accuracy / confusion: 69.83% / [[101, 129], [49, 311]] ------------------------------ Epoch 115 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.472487 - Iter 028 / 029, Loss: 0.272754 * Train accuracy / confusion: 81.68% / [[266, 95], [75, 492]], * Val accuracy / confusion: 65.25% / [[46, 184], [21, 339]] ------------------------------ Epoch 116 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.257556 - Iter 028 / 029, Loss: 0.405379 * Train accuracy / confusion: 82.97% / [[272, 87], [71, 498]], * Val accuracy / confusion: 68.47% / [[161, 69], [117, 243]] ------------------------------ Epoch 117 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.342884 - Iter 028 / 029, Loss: 0.421663 * Train accuracy / confusion: 85.13% / [[285, 75], [63, 505]], * Val accuracy / confusion: 71.69% / [[128, 102], [65, 295]] ------------------------------ Epoch 118 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.272144 - Iter 028 / 029, Loss: 0.443755 * Train accuracy / confusion: 83.94% / [[279, 79], [70, 500]], * Val accuracy / confusion: 68.98% / [[89, 141], [42, 318]] ------------------------------ Epoch 119 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.333219 - Iter 028 / 029, Loss: 0.342753 * Train accuracy / confusion: 83.19% / [[286, 70], [86, 486]], * Val accuracy / confusion: 69.66% / [[141, 89], [90, 270]] ------------------------------ Epoch 120 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.326050 - Iter 028 / 029, Loss: 0.503710 * Train accuracy / confusion: 82.97% / [[272, 93], [65, 498]], * Val accuracy / confusion: 69.66% / [[102, 128], [51, 309]] ------------------------------ Epoch 121 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.282524 - Iter 028 / 029, Loss: 0.466788 * Train accuracy / confusion: 83.30% / [[271, 90], [65, 502]], * Val accuracy / confusion: 70.51% / [[147, 83], [91, 269]] ------------------------------ Epoch 122 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.404907 - Iter 028 / 029, Loss: 0.478892 * Train accuracy / confusion: 82.97% / [[280, 76], [82, 490]], * Val accuracy / confusion: 71.36% / [[154, 76], [93, 267]] ------------------------------ Epoch 123 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.534379 - Iter 028 / 029, Loss: 0.332228 * Train accuracy / confusion: 84.38% / [[293, 67], [78, 490]], * Val accuracy / confusion: 64.41% / [[195, 35], [175, 185]] ------------------------------ Epoch 124 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.451864 - Iter 028 / 029, Loss: 0.287160 * Train accuracy / confusion: 84.91% / [[280, 84], [56, 508]], * Val accuracy / confusion: 65.25% / [[163, 67], [138, 222]] ------------------------------ Epoch 125 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.389161 - Iter 028 / 029, Loss: 0.338519 * Train accuracy / confusion: 83.19% / [[290, 76], [80, 482]], * Val accuracy / confusion: 64.58% / [[189, 41], [168, 192]] ------------------------------ Epoch 126 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.354309 - Iter 028 / 029, Loss: 0.517235 * Train accuracy / confusion: 84.38% / [[285, 75], [70, 498]], * Val accuracy / confusion: 68.64% / [[174, 56], [129, 231]] ------------------------------ Epoch 127 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.422527 - Iter 028 / 029, Loss: 0.333713 * Train accuracy / confusion: 83.41% / [[282, 79], [75, 492]], * Val accuracy / confusion: 69.15% / [[118, 112], [70, 290]] ------------------------------ Epoch 128 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.550026 - Iter 028 / 029, Loss: 0.489340 * Train accuracy / confusion: 85.56% / [[299, 69], [65, 495]], * Val accuracy / confusion: 67.29% / [[176, 54], [139, 221]] ------------------------------ Epoch 129 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.247807 - Iter 028 / 029, Loss: 0.265827 * Train accuracy / confusion: 83.73% / [[270, 91], [60, 507]], * Val accuracy / confusion: 66.10% / [[192, 38], [162, 198]] ------------------------------ Epoch 130 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.329818 - Iter 028 / 029, Loss: 0.318204 * Train accuracy / confusion: 85.88% / [[290, 70], [61, 507]], * Val accuracy / confusion: 64.41% / [[183, 47], [163, 197]] ------------------------------ Epoch 131 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.344036 - Iter 028 / 029, Loss: 0.334493 * Train accuracy / confusion: 83.84% / [[289, 69], [81, 489]], * Val accuracy / confusion: 64.75% / [[161, 69], [139, 221]] ------------------------------ Epoch 132 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.456120 - Iter 028 / 029, Loss: 0.416587 * Train accuracy / confusion: 84.59% / [[285, 79], [64, 500]], * Val accuracy / confusion: 70.34% / [[154, 76], [99, 261]] ------------------------------ Epoch 133 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.319144 - Iter 028 / 029, Loss: 0.353843 * Train accuracy / confusion: 84.38% / [[284, 75], [70, 499]], * Val accuracy / confusion: 68.14% / [[121, 109], [79, 281]] ------------------------------ Epoch 134 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.381113 - Iter 028 / 029, Loss: 0.359172 * Train accuracy / confusion: 83.84% / [[289, 72], [78, 489]], * Val accuracy / confusion: 69.32% / [[146, 84], [97, 263]] ------------------------------ Epoch 135 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.395957 - Iter 028 / 029, Loss: 0.577980 * Train accuracy / confusion: 84.81% / [[282, 79], [62, 505]], * Val accuracy / confusion: 67.97% / [[184, 46], [143, 217]] ------------------------------ Epoch 136 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.273281 - Iter 028 / 029, Loss: 0.238936 * Train accuracy / confusion: 85.34% / [[290, 73], [63, 502]], * Val accuracy / confusion: 67.46% / [[169, 61], [131, 229]] ------------------------------ Epoch 137 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.547633 - Iter 028 / 029, Loss: 0.298220 * Train accuracy / confusion: 84.38% / [[287, 76], [69, 496]], * Val accuracy / confusion: 66.44% / [[79, 151], [47, 313]] ------------------------------ Epoch 138 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.189201 - Iter 028 / 029, Loss: 0.504941 * Train accuracy / confusion: 85.78% / [[292, 74], [58, 504]], * Val accuracy / confusion: 67.63% / [[144, 86], [105, 255]] ------------------------------ Epoch 139 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.399512 - Iter 028 / 029, Loss: 0.504220 * Train accuracy / confusion: 84.70% / [[296, 66], [76, 490]], * Val accuracy / confusion: 58.47% / [[203, 27], [218, 142]] ------------------------------ Epoch 140 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.321730 - Iter 028 / 029, Loss: 0.420756 * Train accuracy / confusion: 84.48% / [[292, 74], [70, 492]], * Val accuracy / confusion: 69.66% / [[153, 77], [102, 258]] ------------------------------ Epoch 141 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.278959 - Iter 028 / 029, Loss: 0.269391 * Train accuracy / confusion: 85.78% / [[293, 70], [62, 503]], * Val accuracy / confusion: 72.88% / [[132, 98], [62, 298]] ------------------------------ Epoch 142 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.422691 - Iter 028 / 029, Loss: 0.381092 * Train accuracy / confusion: 84.59% / [[297, 71], [72, 488]], * Val accuracy / confusion: 66.61% / [[100, 130], [67, 293]] ------------------------------ Epoch 143 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.214041 - Iter 028 / 029, Loss: 0.335773 * Train accuracy / confusion: 86.64% / [[300, 62], [62, 504]], * Val accuracy / confusion: 67.29% / [[149, 81], [112, 248]] ------------------------------ Epoch 144 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.248449 - Iter 028 / 029, Loss: 0.299402 * Train accuracy / confusion: 88.04% / [[301, 58], [53, 516]], * Val accuracy / confusion: 67.46% / [[149, 81], [111, 249]] ------------------------------ Epoch 145 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.195656 - Iter 028 / 029, Loss: 0.202589 * Train accuracy / confusion: 86.21% / [[293, 71], [57, 507]], * Val accuracy / confusion: 64.58% / [[101, 129], [80, 280]] ------------------------------ Epoch 146 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.413664 - Iter 028 / 029, Loss: 0.344944 * Train accuracy / confusion: 85.24% / [[289, 76], [61, 502]], * Val accuracy / confusion: 67.12% / [[89, 141], [53, 307]] ------------------------------ Epoch 147 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.288344 - Iter 028 / 029, Loss: 0.320950 * Train accuracy / confusion: 85.24% / [[306, 59], [78, 485]], * Val accuracy / confusion: 64.92% / [[183, 47], [160, 200]] ------------------------------ Epoch 148 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.275301 - Iter 028 / 029, Loss: 0.291671 * Train accuracy / confusion: 86.21% / [[299, 66], [62, 501]], * Val accuracy / confusion: 63.39% / [[172, 58], [158, 202]] ------------------------------ Epoch 149 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.466664 - Iter 028 / 029, Loss: 0.302280 * Train accuracy / confusion: 86.42% / [[297, 65], [61, 505]], * Val accuracy / confusion: 68.31% / [[184, 46], [141, 219]] ------------------------------ Epoch 150 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.226072 - Iter 028 / 029, Loss: 0.216319 * Train accuracy / confusion: 87.39% / [[310, 49], [68, 501]], * Val accuracy / confusion: 66.61% / [[79, 151], [46, 314]] ------------------------------ Epoch 151 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.699895 - Iter 028 / 029, Loss: 0.199211 * Train accuracy / confusion: 86.42% / [[288, 71], [55, 514]], * Val accuracy / confusion: 67.46% / [[87, 143], [49, 311]] ------------------------------ Epoch 152 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.295981 - Iter 028 / 029, Loss: 0.258515 * Train accuracy / confusion: 86.85% / [[301, 60], [62, 505]], * Val accuracy / confusion: 66.61% / [[59, 171], [26, 334]] ------------------------------ Epoch 153 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.238793 - Iter 028 / 029, Loss: 0.344754 * Train accuracy / confusion: 85.67% / [[293, 71], [62, 502]], * Val accuracy / confusion: 66.44% / [[116, 114], [84, 276]] ------------------------------ Epoch 154 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.158690 - Iter 028 / 029, Loss: 0.376459 * Train accuracy / confusion: 85.67% / [[291, 67], [66, 504]], * Val accuracy / confusion: 65.25% / [[186, 44], [161, 199]] ------------------------------ Epoch 155 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.384114 - Iter 028 / 029, Loss: 0.302094 * Train accuracy / confusion: 86.53% / [[294, 65], [60, 509]], * Val accuracy / confusion: 66.95% / [[126, 104], [91, 269]] ------------------------------ Epoch 156 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.291608 - Iter 028 / 029, Loss: 0.261074 * Train accuracy / confusion: 87.28% / [[291, 68], [50, 519]], * Val accuracy / confusion: 66.61% / [[111, 119], [78, 282]] ------------------------------ Epoch 157 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.464103 - Iter 028 / 029, Loss: 0.277254 * Train accuracy / confusion: 87.50% / [[310, 51], [65, 502]], * Val accuracy / confusion: 63.90% / [[62, 168], [45, 315]] ------------------------------ Epoch 158 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.249488 - Iter 028 / 029, Loss: 0.226457 * Train accuracy / confusion: 85.78% / [[303, 56], [76, 493]], * Val accuracy / confusion: 64.41% / [[68, 162], [48, 312]] ------------------------------ Epoch 159 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.208204 - Iter 028 / 029, Loss: 0.209639 * Train accuracy / confusion: 86.85% / [[298, 63], [59, 508]], * Val accuracy / confusion: 69.49% / [[119, 111], [69, 291]] ------------------------------ Epoch 160 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.198411 - Iter 028 / 029, Loss: 0.346820 * Train accuracy / confusion: 86.75% / [[297, 63], [60, 508]], * Val accuracy / confusion: 61.69% / [[210, 20], [206, 154]] ------------------------------ Epoch 161 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.333941 - Iter 028 / 029, Loss: 0.255824 * Train accuracy / confusion: 87.50% / [[306, 56], [60, 506]], * Val accuracy / confusion: 65.25% / [[158, 72], [133, 227]] ------------------------------ Epoch 162 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.256804 - Iter 028 / 029, Loss: 0.372789 * Train accuracy / confusion: 87.61% / [[314, 46], [69, 499]], * Val accuracy / confusion: 67.97% / [[135, 95], [94, 266]] ------------------------------ Epoch 163 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.386975 - Iter 028 / 029, Loss: 0.336763 * Train accuracy / confusion: 87.50% / [[309, 56], [60, 503]], * Val accuracy / confusion: 64.58% / [[112, 118], [91, 269]] ------------------------------ Epoch 164 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.212633 - Iter 028 / 029, Loss: 0.342612 * Train accuracy / confusion: 87.72% / [[307, 59], [55, 507]], * Val accuracy / confusion: 69.49% / [[173, 57], [123, 237]] ------------------------------ Epoch 165 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.233889 - Iter 028 / 029, Loss: 0.269753 * Train accuracy / confusion: 87.18% / [[308, 56], [63, 501]], * Val accuracy / confusion: 68.14% / [[152, 78], [110, 250]] ------------------------------ Epoch 166 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.344047 - Iter 028 / 029, Loss: 0.296857 * Train accuracy / confusion: 87.50% / [[306, 53], [63, 506]], * Val accuracy / confusion: 66.78% / [[179, 51], [145, 215]] ------------------------------ Epoch 167 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.308858 - Iter 028 / 029, Loss: 0.462263 * Train accuracy / confusion: 87.93% / [[303, 57], [55, 513]], * Val accuracy / confusion: 70.17% / [[142, 88], [88, 272]] ------------------------------ Epoch 168 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.250379 - Iter 028 / 029, Loss: 0.279839 * Train accuracy / confusion: 88.15% / [[305, 54], [56, 513]], * Val accuracy / confusion: 68.47% / [[152, 78], [108, 252]] ------------------------------ Epoch 169 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.223579 - Iter 028 / 029, Loss: 0.301549 * Train accuracy / confusion: 89.22% / [[305, 54], [46, 523]], * Val accuracy / confusion: 64.75% / [[41, 189], [19, 341]] ------------------------------ Epoch 170 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.298039 - Iter 028 / 029, Loss: 0.455180 * Train accuracy / confusion: 87.61% / [[315, 45], [70, 498]], * Val accuracy / confusion: 63.73% / [[114, 116], [98, 262]] ------------------------------ Epoch 171 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.236673 - Iter 028 / 029, Loss: 0.150578 * Train accuracy / confusion: 90.84% / [[311, 50], [35, 532]], * Val accuracy / confusion: 68.64% / [[87, 143], [42, 318]] ------------------------------ Epoch 172 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.290936 - Iter 028 / 029, Loss: 0.567865 * Train accuracy / confusion: 86.31% / [[295, 65], [62, 506]], * Val accuracy / confusion: 67.12% / [[133, 97], [97, 263]] ------------------------------ Epoch 173 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.305743 - Iter 028 / 029, Loss: 0.270098 * Train accuracy / confusion: 88.69% / [[309, 51], [54, 514]], * Val accuracy / confusion: 67.63% / [[161, 69], [122, 238]] ------------------------------ Epoch 174 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.298845 - Iter 028 / 029, Loss: 0.190199 * Train accuracy / confusion: 88.47% / [[308, 57], [50, 513]], * Val accuracy / confusion: 65.76% / [[126, 104], [98, 262]] ------------------------------ Epoch 175 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.251994 - Iter 028 / 029, Loss: 0.167260 * Train accuracy / confusion: 87.39% / [[307, 59], [58, 504]], * Val accuracy / confusion: 68.14% / [[196, 34], [154, 206]] ------------------------------ Epoch 176 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.249497 - Iter 028 / 029, Loss: 0.271924 * Train accuracy / confusion: 88.69% / [[306, 58], [47, 517]], * Val accuracy / confusion: 67.63% / [[161, 69], [122, 238]] ------------------------------ Epoch 177 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.398975 - Iter 028 / 029, Loss: 0.507382 * Train accuracy / confusion: 86.53% / [[308, 52], [73, 495]], * Val accuracy / confusion: 66.10% / [[126, 104], [96, 264]] ------------------------------ Epoch 178 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.209534 - Iter 028 / 029, Loss: 0.107570 * Train accuracy / confusion: 89.12% / [[304, 57], [44, 523]], * Val accuracy / confusion: 67.29% / [[138, 92], [101, 259]] ------------------------------ Epoch 179 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.316584 - Iter 028 / 029, Loss: 0.315712 * Train accuracy / confusion: 88.47% / [[320, 44], [63, 501]], * Val accuracy / confusion: 72.71% / [[141, 89], [72, 288]] ------------------------------ Epoch 180 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.251558 - Iter 028 / 029, Loss: 0.159415 * Train accuracy / confusion: 87.39% / [[303, 56], [61, 508]], * Val accuracy / confusion: 69.66% / [[143, 87], [92, 268]] ------------------------------ Epoch 181 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.148833 - Iter 028 / 029, Loss: 0.353846 * Train accuracy / confusion: 90.62% / [[311, 52], [35, 530]], * Val accuracy / confusion: 67.63% / [[136, 94], [97, 263]] ------------------------------ Epoch 182 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.244768 - Iter 028 / 029, Loss: 0.407765 * Train accuracy / confusion: 86.42% / [[295, 69], [57, 507]], * Val accuracy / confusion: 64.41% / [[78, 152], [58, 302]] ------------------------------ Epoch 183 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.557929 - Iter 028 / 029, Loss: 0.500565 * Train accuracy / confusion: 89.76% / [[318, 44], [51, 515]], * Val accuracy / confusion: 70.17% / [[175, 55], [121, 239]] ------------------------------ Epoch 184 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.462278 - Iter 028 / 029, Loss: 0.335811 * Train accuracy / confusion: 89.76% / [[304, 57], [38, 529]], * Val accuracy / confusion: 66.10% / [[98, 132], [68, 292]] ------------------------------ Epoch 185 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.191668 - Iter 028 / 029, Loss: 0.339806 * Train accuracy / confusion: 89.66% / [[312, 55], [41, 520]], * Val accuracy / confusion: 70.17% / [[111, 119], [57, 303]] ------------------------------ Epoch 186 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.346722 - Iter 028 / 029, Loss: 0.157116 * Train accuracy / confusion: 89.22% / [[318, 44], [56, 510]], * Val accuracy / confusion: 67.97% / [[116, 114], [75, 285]] ------------------------------ Epoch 187 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.134918 - Iter 028 / 029, Loss: 0.173082 * Train accuracy / confusion: 89.66% / [[312, 47], [49, 520]], * Val accuracy / confusion: 67.80% / [[77, 153], [37, 323]] ------------------------------ Epoch 188 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.352494 - Iter 028 / 029, Loss: 0.207912 * Train accuracy / confusion: 89.44% / [[311, 51], [47, 519]], * Val accuracy / confusion: 62.71% / [[35, 195], [25, 335]] ------------------------------ Epoch 189 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.189298 - Iter 028 / 029, Loss: 0.260793 * Train accuracy / confusion: 89.76% / [[312, 47], [48, 521]], * Val accuracy / confusion: 66.95% / [[70, 160], [35, 325]] ------------------------------ Epoch 190 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.344591 - Iter 028 / 029, Loss: 0.390861 * Train accuracy / confusion: 87.28% / [[302, 60], [58, 508]], * Val accuracy / confusion: 67.63% / [[166, 64], [127, 233]] ------------------------------ Epoch 191 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.230010 - Iter 028 / 029, Loss: 0.352146 * Train accuracy / confusion: 90.19% / [[323, 39], [52, 514]], * Val accuracy / confusion: 68.81% / [[138, 92], [92, 268]] ------------------------------ Epoch 192 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.330768 - Iter 028 / 029, Loss: 0.151059 * Train accuracy / confusion: 89.44% / [[301, 60], [38, 529]], * Val accuracy / confusion: 67.46% / [[127, 103], [89, 271]] ------------------------------ Epoch 193 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.165878 - Iter 028 / 029, Loss: 0.203514 * Train accuracy / confusion: 89.98% / [[313, 49], [44, 522]], * Val accuracy / confusion: 63.22% / [[66, 164], [53, 307]] ------------------------------ Epoch 194 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.447083 - Iter 028 / 029, Loss: 0.149899 * Train accuracy / confusion: 91.38% / [[326, 34], [46, 522]], * Val accuracy / confusion: 67.97% / [[143, 87], [102, 258]] ------------------------------ Epoch 195 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.188304 - Iter 028 / 029, Loss: 0.354513 * Train accuracy / confusion: 88.90% / [[312, 52], [51, 513]], * Val accuracy / confusion: 69.15% / [[170, 60], [122, 238]] ------------------------------ Epoch 196 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.285534 - Iter 028 / 029, Loss: 0.245993 * Train accuracy / confusion: 88.15% / [[302, 58], [52, 516]], * Val accuracy / confusion: 69.15% / [[156, 74], [108, 252]] ------------------------------ Epoch 197 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.299743 - Iter 028 / 029, Loss: 0.255037 * Train accuracy / confusion: 87.93% / [[302, 54], [58, 514]], * Val accuracy / confusion: 67.97% / [[70, 160], [29, 331]] ------------------------------ Epoch 198 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.292798 - Iter 028 / 029, Loss: 0.247240 * Train accuracy / confusion: 90.30% / [[312, 45], [45, 526]], * Val accuracy / confusion: 62.54% / [[180, 50], [171, 189]] ------------------------------ Epoch 199 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.150653 - Iter 028 / 029, Loss: 0.146133 * Train accuracy / confusion: 89.55% / [[316, 44], [53, 515]], * Val accuracy / confusion: 71.02% / [[126, 104], [67, 293]] ------------------------------ Epoch 200 / 500, Learning rate: 1.49e-04 ------------------------------ - Iter 014 / 029, Loss: 0.221510 - Iter 028 / 029, Loss: 0.212695 * Train accuracy / confusion: 89.87% / [[316, 48], [46, 518]], * Val accuracy / confusion: 67.29% / [[110, 120], [73, 287]] ------------------------------ Epoch 201 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.245681 - Iter 028 / 029, Loss: 0.198154 * Train accuracy / confusion: 90.62% / [[320, 43], [44, 521]], * Val accuracy / confusion: 65.08% / [[114, 116], [90, 270]] ------------------------------ Epoch 202 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.216229 - Iter 028 / 029, Loss: 0.265782 * Train accuracy / confusion: 90.73% / [[314, 44], [42, 528]], * Val accuracy / confusion: 66.95% / [[139, 91], [104, 256]] ------------------------------ Epoch 203 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.074399 - Iter 028 / 029, Loss: 0.267615 * Train accuracy / confusion: 93.32% / [[334, 29], [33, 532]], * Val accuracy / confusion: 67.46% / [[137, 93], [99, 261]] ------------------------------ Epoch 204 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.197936 - Iter 028 / 029, Loss: 0.198080 * Train accuracy / confusion: 92.89% / [[321, 40], [26, 541]], * Val accuracy / confusion: 69.83% / [[130, 100], [78, 282]] ------------------------------ Epoch 205 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.129473 - Iter 028 / 029, Loss: 0.150447 * Train accuracy / confusion: 93.21% / [[331, 30], [33, 534]], * Val accuracy / confusion: 68.81% / [[131, 99], [85, 275]] ------------------------------ Epoch 206 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.130029 - Iter 028 / 029, Loss: 0.236175 * Train accuracy / confusion: 92.35% / [[332, 30], [41, 525]], * Val accuracy / confusion: 66.95% / [[129, 101], [94, 266]] ------------------------------ Epoch 207 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.134315 - Iter 028 / 029, Loss: 0.195383 * Train accuracy / confusion: 91.16% / [[325, 36], [46, 521]], * Val accuracy / confusion: 66.44% / [[135, 95], [103, 257]] ------------------------------ Epoch 208 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.146084 - Iter 028 / 029, Loss: 0.146233 * Train accuracy / confusion: 91.81% / [[321, 35], [41, 531]], * Val accuracy / confusion: 65.59% / [[128, 102], [101, 259]] ------------------------------ Epoch 209 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.127071 - Iter 028 / 029, Loss: 0.222285 * Train accuracy / confusion: 93.32% / [[335, 27], [35, 531]], * Val accuracy / confusion: 69.15% / [[135, 95], [87, 273]] ------------------------------ Epoch 210 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.148558 - Iter 028 / 029, Loss: 0.119990 * Train accuracy / confusion: 91.59% / [[328, 32], [46, 522]], * Val accuracy / confusion: 66.27% / [[128, 102], [97, 263]] ------------------------------ Epoch 211 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.099962 - Iter 028 / 029, Loss: 0.158786 * Train accuracy / confusion: 92.67% / [[328, 32], [36, 532]], * Val accuracy / confusion: 66.78% / [[125, 105], [91, 269]] ------------------------------ Epoch 212 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.188296 - Iter 028 / 029, Loss: 0.197790 * Train accuracy / confusion: 92.24% / [[323, 40], [32, 533]], * Val accuracy / confusion: 67.29% / [[121, 109], [84, 276]] ------------------------------ Epoch 213 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.093040 - Iter 028 / 029, Loss: 0.124372 * Train accuracy / confusion: 92.46% / [[323, 40], [30, 535]], * Val accuracy / confusion: 68.31% / [[132, 98], [89, 271]] ------------------------------ Epoch 214 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.096362 - Iter 028 / 029, Loss: 0.488023 * Train accuracy / confusion: 91.70% / [[320, 43], [34, 531]], * Val accuracy / confusion: 68.64% / [[125, 105], [80, 280]] ------------------------------ Epoch 215 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.189497 - Iter 028 / 029, Loss: 0.276003 * Train accuracy / confusion: 94.07% / [[336, 25], [30, 537]], * Val accuracy / confusion: 67.12% / [[125, 105], [89, 271]] ------------------------------ Epoch 216 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.125251 - Iter 028 / 029, Loss: 0.224155 * Train accuracy / confusion: 93.00% / [[333, 30], [35, 530]], * Val accuracy / confusion: 66.78% / [[137, 93], [103, 257]] ------------------------------ Epoch 217 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.174248 - Iter 028 / 029, Loss: 0.237291 * Train accuracy / confusion: 92.67% / [[331, 34], [34, 529]], * Val accuracy / confusion: 67.80% / [[122, 108], [82, 278]] ------------------------------ Epoch 218 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.120693 - Iter 028 / 029, Loss: 0.095341 * Train accuracy / confusion: 93.53% / [[321, 37], [23, 547]], * Val accuracy / confusion: 66.61% / [[117, 113], [84, 276]] ------------------------------ Epoch 219 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.207671 - Iter 028 / 029, Loss: 0.270938 * Train accuracy / confusion: 93.75% / [[335, 27], [31, 535]], * Val accuracy / confusion: 68.14% / [[132, 98], [90, 270]] ------------------------------ Epoch 220 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.073073 - Iter 028 / 029, Loss: 0.102357 * Train accuracy / confusion: 94.72% / [[342, 20], [29, 537]], * Val accuracy / confusion: 70.17% / [[138, 92], [84, 276]] ------------------------------ Epoch 221 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.117605 - Iter 028 / 029, Loss: 0.175003 * Train accuracy / confusion: 93.53% / [[336, 30], [30, 532]], * Val accuracy / confusion: 68.47% / [[114, 116], [70, 290]] ------------------------------ Epoch 222 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.172580 - Iter 028 / 029, Loss: 0.198927 * Train accuracy / confusion: 92.46% / [[326, 39], [31, 532]], * Val accuracy / confusion: 72.03% / [[144, 86], [79, 281]] ------------------------------ Epoch 223 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.179086 - Iter 028 / 029, Loss: 0.277608 * Train accuracy / confusion: 93.86% / [[336, 27], [30, 535]], * Val accuracy / confusion: 69.49% / [[139, 91], [89, 271]] ------------------------------ Epoch 224 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.172773 - Iter 028 / 029, Loss: 0.191333 * Train accuracy / confusion: 93.86% / [[343, 18], [39, 528]], * Val accuracy / confusion: 69.15% / [[142, 88], [94, 266]] ------------------------------ Epoch 225 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.166858 - Iter 028 / 029, Loss: 0.178868 * Train accuracy / confusion: 92.67% / [[331, 30], [38, 529]], * Val accuracy / confusion: 70.34% / [[138, 92], [83, 277]] ------------------------------ Epoch 226 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.166488 - Iter 028 / 029, Loss: 0.113830 * Train accuracy / confusion: 93.43% / [[324, 31], [30, 543]], * Val accuracy / confusion: 65.76% / [[133, 97], [105, 255]] ------------------------------ Epoch 227 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.306722 - Iter 028 / 029, Loss: 0.246319 * Train accuracy / confusion: 91.38% / [[325, 38], [42, 523]], * Val accuracy / confusion: 67.46% / [[124, 106], [86, 274]] ------------------------------ Epoch 228 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.182264 - Iter 028 / 029, Loss: 0.085696 * Train accuracy / confusion: 92.46% / [[329, 34], [36, 529]], * Val accuracy / confusion: 68.64% / [[127, 103], [82, 278]] ------------------------------ Epoch 229 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.163424 - Iter 028 / 029, Loss: 0.072657 * Train accuracy / confusion: 93.43% / [[329, 31], [30, 538]], * Val accuracy / confusion: 67.12% / [[122, 108], [86, 274]] ------------------------------ Epoch 230 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.104993 - Iter 028 / 029, Loss: 0.097346 * Train accuracy / confusion: 93.43% / [[334, 32], [29, 533]], * Val accuracy / confusion: 64.92% / [[118, 112], [95, 265]] ------------------------------ Epoch 231 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.203788 - Iter 028 / 029, Loss: 0.136441 * Train accuracy / confusion: 92.13% / [[325, 34], [39, 530]], * Val accuracy / confusion: 66.78% / [[135, 95], [101, 259]] ------------------------------ Epoch 232 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.442221 - Iter 028 / 029, Loss: 0.082997 * Train accuracy / confusion: 92.46% / [[326, 34], [36, 532]], * Val accuracy / confusion: 66.61% / [[127, 103], [94, 266]] ------------------------------ Epoch 233 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.161982 - Iter 028 / 029, Loss: 0.372716 * Train accuracy / confusion: 92.56% / [[327, 36], [33, 532]], * Val accuracy / confusion: 71.86% / [[137, 93], [73, 287]] ------------------------------ Epoch 234 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.276014 - Iter 028 / 029, Loss: 0.137623 * Train accuracy / confusion: 92.78% / [[332, 31], [36, 529]], * Val accuracy / confusion: 67.80% / [[133, 97], [93, 267]] ------------------------------ Epoch 235 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.398964 - Iter 028 / 029, Loss: 0.119960 * Train accuracy / confusion: 93.75% / [[332, 32], [26, 538]], * Val accuracy / confusion: 68.64% / [[138, 92], [93, 267]] ------------------------------ Epoch 236 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.206756 - Iter 028 / 029, Loss: 0.155077 * Train accuracy / confusion: 93.21% / [[335, 27], [36, 530]], * Val accuracy / confusion: 67.80% / [[125, 105], [85, 275]] ------------------------------ Epoch 237 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.133101 - Iter 028 / 029, Loss: 0.135502 * Train accuracy / confusion: 92.35% / [[332, 31], [40, 525]], * Val accuracy / confusion: 67.12% / [[139, 91], [103, 257]] ------------------------------ Epoch 238 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.214141 - Iter 028 / 029, Loss: 0.099601 * Train accuracy / confusion: 93.00% / [[334, 29], [36, 529]], * Val accuracy / confusion: 68.98% / [[144, 86], [97, 263]] ------------------------------ Epoch 239 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.127974 - Iter 028 / 029, Loss: 0.338738 * Train accuracy / confusion: 94.50% / [[337, 22], [29, 540]], * Val accuracy / confusion: 67.80% / [[124, 106], [84, 276]] ------------------------------ Epoch 240 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.119655 - Iter 028 / 029, Loss: 0.101119 * Train accuracy / confusion: 93.97% / [[339, 25], [31, 533]], * Val accuracy / confusion: 66.61% / [[130, 100], [97, 263]] ------------------------------ Epoch 241 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.204424 - Iter 028 / 029, Loss: 0.172048 * Train accuracy / confusion: 93.32% / [[335, 29], [33, 531]], * Val accuracy / confusion: 68.64% / [[136, 94], [91, 269]] ------------------------------ Epoch 242 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.173742 - Iter 028 / 029, Loss: 0.065725 * Train accuracy / confusion: 92.67% / [[330, 36], [32, 530]], * Val accuracy / confusion: 68.81% / [[123, 107], [77, 283]] ------------------------------ Epoch 243 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.152816 - Iter 028 / 029, Loss: 0.163276 * Train accuracy / confusion: 92.46% / [[329, 36], [34, 529]], * Val accuracy / confusion: 66.10% / [[115, 115], [85, 275]] ------------------------------ Epoch 244 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.152566 - Iter 028 / 029, Loss: 0.079197 * Train accuracy / confusion: 94.50% / [[338, 26], [25, 539]], * Val accuracy / confusion: 70.34% / [[139, 91], [84, 276]] ------------------------------ Epoch 245 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.222750 - Iter 028 / 029, Loss: 0.149120 * Train accuracy / confusion: 92.78% / [[327, 37], [30, 534]], * Val accuracy / confusion: 67.12% / [[123, 107], [87, 273]] ------------------------------ Epoch 246 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.168424 - Iter 028 / 029, Loss: 0.098889 * Train accuracy / confusion: 94.29% / [[336, 24], [29, 539]], * Val accuracy / confusion: 70.00% / [[136, 94], [83, 277]] ------------------------------ Epoch 247 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.187425 - Iter 028 / 029, Loss: 0.176582 * Train accuracy / confusion: 93.00% / [[336, 26], [39, 527]], * Val accuracy / confusion: 69.66% / [[142, 88], [91, 269]] ------------------------------ Epoch 248 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.117041 - Iter 028 / 029, Loss: 0.108389 * Train accuracy / confusion: 92.78% / [[326, 38], [29, 535]], * Val accuracy / confusion: 70.68% / [[134, 96], [77, 283]] ------------------------------ Epoch 249 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.107712 - Iter 028 / 029, Loss: 0.108915 * Train accuracy / confusion: 93.86% / [[334, 27], [30, 537]], * Val accuracy / confusion: 68.81% / [[152, 78], [106, 254]] ------------------------------ Epoch 250 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.199921 - Iter 028 / 029, Loss: 0.073311 * Train accuracy / confusion: 93.97% / [[336, 25], [31, 536]], * Val accuracy / confusion: 65.76% / [[115, 115], [87, 273]] ------------------------------ Epoch 251 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.151570 - Iter 028 / 029, Loss: 0.105981 * Train accuracy / confusion: 93.75% / [[335, 27], [31, 535]], * Val accuracy / confusion: 67.46% / [[130, 100], [92, 268]] ------------------------------ Epoch 252 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.277553 - Iter 028 / 029, Loss: 0.052066 * Train accuracy / confusion: 94.18% / [[332, 30], [24, 542]], * Val accuracy / confusion: 68.64% / [[138, 92], [93, 267]] ------------------------------ Epoch 253 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.104339 - Iter 028 / 029, Loss: 0.201691 * Train accuracy / confusion: 94.29% / [[335, 28], [25, 540]], * Val accuracy / confusion: 70.68% / [[142, 88], [85, 275]] ------------------------------ Epoch 254 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.073859 - Iter 028 / 029, Loss: 0.095009 * Train accuracy / confusion: 94.40% / [[339, 24], [28, 537]], * Val accuracy / confusion: 67.63% / [[134, 96], [95, 265]] ------------------------------ Epoch 255 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.078362 - Iter 028 / 029, Loss: 0.065202 * Train accuracy / confusion: 94.61% / [[341, 26], [24, 537]], * Val accuracy / confusion: 67.29% / [[131, 99], [94, 266]] ------------------------------ Epoch 256 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.320556 - Iter 028 / 029, Loss: 0.203148 * Train accuracy / confusion: 93.00% / [[330, 31], [34, 533]], * Val accuracy / confusion: 66.10% / [[105, 125], [75, 285]] ------------------------------ Epoch 257 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.299358 - Iter 028 / 029, Loss: 0.118433 * Train accuracy / confusion: 93.00% / [[332, 28], [37, 531]], * Val accuracy / confusion: 65.42% / [[134, 96], [108, 252]] ------------------------------ Epoch 258 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.277803 - Iter 028 / 029, Loss: 0.203415 * Train accuracy / confusion: 93.43% / [[331, 31], [30, 536]], * Val accuracy / confusion: 68.14% / [[136, 94], [94, 266]] ------------------------------ Epoch 259 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.290558 - Iter 028 / 029, Loss: 0.113204 * Train accuracy / confusion: 94.29% / [[338, 23], [30, 537]], * Val accuracy / confusion: 70.68% / [[147, 83], [90, 270]] ------------------------------ Epoch 260 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.062951 - Iter 028 / 029, Loss: 0.124209 * Train accuracy / confusion: 94.50% / [[337, 24], [27, 540]], * Val accuracy / confusion: 68.98% / [[127, 103], [80, 280]] ------------------------------ Epoch 261 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.208319 - Iter 028 / 029, Loss: 0.208305 * Train accuracy / confusion: 93.10% / [[331, 30], [34, 533]], * Val accuracy / confusion: 67.63% / [[128, 102], [89, 271]] ------------------------------ Epoch 262 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.237891 - Iter 028 / 029, Loss: 0.045795 * Train accuracy / confusion: 95.26% / [[336, 26], [18, 548]], * Val accuracy / confusion: 68.81% / [[127, 103], [81, 279]] ------------------------------ Epoch 263 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.115186 - Iter 028 / 029, Loss: 0.095934 * Train accuracy / confusion: 94.72% / [[337, 25], [24, 542]], * Val accuracy / confusion: 69.32% / [[156, 74], [107, 253]] ------------------------------ Epoch 264 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.297355 - Iter 028 / 029, Loss: 0.174365 * Train accuracy / confusion: 93.97% / [[335, 27], [29, 537]], * Val accuracy / confusion: 68.14% / [[137, 93], [95, 265]] ------------------------------ Epoch 265 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.115095 - Iter 028 / 029, Loss: 0.080321 * Train accuracy / confusion: 94.29% / [[344, 21], [32, 531]], * Val accuracy / confusion: 65.08% / [[138, 92], [114, 246]] ------------------------------ Epoch 266 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.135070 - Iter 028 / 029, Loss: 0.061624 * Train accuracy / confusion: 93.10% / [[332, 32], [32, 532]], * Val accuracy / confusion: 69.49% / [[141, 89], [91, 269]] ------------------------------ Epoch 267 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.236065 - Iter 028 / 029, Loss: 0.151892 * Train accuracy / confusion: 94.72% / [[338, 25], [24, 541]], * Val accuracy / confusion: 67.97% / [[125, 105], [84, 276]] ------------------------------ Epoch 268 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.108909 - Iter 028 / 029, Loss: 0.145750 * Train accuracy / confusion: 95.15% / [[338, 25], [20, 545]], * Val accuracy / confusion: 68.81% / [[137, 93], [91, 269]] ------------------------------ Epoch 269 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.277018 - Iter 028 / 029, Loss: 0.058410 * Train accuracy / confusion: 94.72% / [[339, 25], [24, 540]], * Val accuracy / confusion: 68.64% / [[125, 105], [80, 280]] ------------------------------ Epoch 270 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.217578 - Iter 028 / 029, Loss: 0.120649 * Train accuracy / confusion: 93.10% / [[337, 28], [36, 527]], * Val accuracy / confusion: 66.78% / [[137, 93], [103, 257]] ------------------------------ Epoch 271 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.180174 - Iter 028 / 029, Loss: 0.315283 * Train accuracy / confusion: 93.53% / [[330, 31], [29, 538]], * Val accuracy / confusion: 69.49% / [[135, 95], [85, 275]] ------------------------------ Epoch 272 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.078259 - Iter 028 / 029, Loss: 0.319443 * Train accuracy / confusion: 94.72% / [[343, 22], [27, 536]], * Val accuracy / confusion: 69.32% / [[147, 83], [98, 262]] ------------------------------ Epoch 273 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.110773 - Iter 028 / 029, Loss: 0.285653 * Train accuracy / confusion: 92.67% / [[326, 36], [32, 534]], * Val accuracy / confusion: 69.66% / [[155, 75], [104, 256]] ------------------------------ Epoch 274 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.247294 - Iter 028 / 029, Loss: 0.077319 * Train accuracy / confusion: 93.43% / [[337, 26], [35, 530]], * Val accuracy / confusion: 66.95% / [[125, 105], [90, 270]] ------------------------------ Epoch 275 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.141183 - Iter 028 / 029, Loss: 0.260665 * Train accuracy / confusion: 94.18% / [[337, 26], [28, 537]], * Val accuracy / confusion: 68.14% / [[145, 85], [103, 257]] ------------------------------ Epoch 276 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.072999 - Iter 028 / 029, Loss: 0.079498 * Train accuracy / confusion: 94.72% / [[340, 19], [30, 539]], * Val accuracy / confusion: 68.31% / [[138, 92], [95, 265]] ------------------------------ Epoch 277 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.347883 - Iter 028 / 029, Loss: 0.280137 * Train accuracy / confusion: 93.75% / [[330, 32], [26, 540]], * Val accuracy / confusion: 69.83% / [[137, 93], [85, 275]] ------------------------------ Epoch 278 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.116975 - Iter 028 / 029, Loss: 0.221052 * Train accuracy / confusion: 93.21% / [[333, 28], [35, 532]], * Val accuracy / confusion: 66.61% / [[110, 120], [77, 283]] ------------------------------ Epoch 279 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.077119 - Iter 028 / 029, Loss: 0.135796 * Train accuracy / confusion: 93.21% / [[338, 25], [38, 527]], * Val accuracy / confusion: 67.46% / [[141, 89], [103, 257]] ------------------------------ Epoch 280 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.260878 - Iter 028 / 029, Loss: 0.194193 * Train accuracy / confusion: 93.43% / [[329, 33], [28, 538]], * Val accuracy / confusion: 69.32% / [[133, 97], [84, 276]] ------------------------------ Epoch 281 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.207053 - Iter 028 / 029, Loss: 0.130438 * Train accuracy / confusion: 94.61% / [[339, 20], [30, 539]], * Val accuracy / confusion: 70.00% / [[142, 88], [89, 271]] ------------------------------ Epoch 282 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.077966 - Iter 028 / 029, Loss: 0.111798 * Train accuracy / confusion: 93.21% / [[332, 29], [34, 533]], * Val accuracy / confusion: 68.81% / [[138, 92], [92, 268]] ------------------------------ Epoch 283 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.243016 - Iter 028 / 029, Loss: 0.174231 * Train accuracy / confusion: 93.86% / [[340, 25], [32, 531]], * Val accuracy / confusion: 68.64% / [[125, 105], [80, 280]] ------------------------------ Epoch 284 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.077370 - Iter 028 / 029, Loss: 0.185974 * Train accuracy / confusion: 92.24% / [[332, 28], [44, 524]], * Val accuracy / confusion: 67.97% / [[136, 94], [95, 265]] ------------------------------ Epoch 285 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.316600 - Iter 028 / 029, Loss: 0.195194 * Train accuracy / confusion: 93.43% / [[334, 27], [34, 533]], * Val accuracy / confusion: 65.93% / [[132, 98], [103, 257]] ------------------------------ Epoch 286 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.096211 - Iter 028 / 029, Loss: 0.252363 * Train accuracy / confusion: 93.10% / [[331, 33], [31, 533]], * Val accuracy / confusion: 67.12% / [[132, 98], [96, 264]] ------------------------------ Epoch 287 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.078949 - Iter 028 / 029, Loss: 0.304050 * Train accuracy / confusion: 94.40% / [[337, 29], [23, 539]], * Val accuracy / confusion: 68.14% / [[145, 85], [103, 257]] ------------------------------ Epoch 288 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.201475 - Iter 028 / 029, Loss: 0.201610 * Train accuracy / confusion: 93.43% / [[333, 29], [32, 534]], * Val accuracy / confusion: 68.64% / [[130, 100], [85, 275]] ------------------------------ Epoch 289 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.590672 - Iter 028 / 029, Loss: 0.254582 * Train accuracy / confusion: 93.97% / [[339, 25], [31, 533]], * Val accuracy / confusion: 66.61% / [[129, 101], [96, 264]] ------------------------------ Epoch 290 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.085779 - Iter 028 / 029, Loss: 0.179386 * Train accuracy / confusion: 94.07% / [[338, 29], [26, 535]], * Val accuracy / confusion: 69.15% / [[138, 92], [90, 270]] ------------------------------ Epoch 291 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.149406 - Iter 028 / 029, Loss: 0.064092 * Train accuracy / confusion: 95.58% / [[346, 14], [27, 541]], * Val accuracy / confusion: 69.83% / [[151, 79], [99, 261]] ------------------------------ Epoch 292 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.174605 - Iter 028 / 029, Loss: 0.145145 * Train accuracy / confusion: 94.94% / [[334, 28], [19, 547]], * Val accuracy / confusion: 68.47% / [[139, 91], [95, 265]] ------------------------------ Epoch 293 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.203311 - Iter 028 / 029, Loss: 0.119308 * Train accuracy / confusion: 94.40% / [[335, 29], [23, 541]], * Val accuracy / confusion: 67.97% / [[134, 96], [93, 267]] ------------------------------ Epoch 294 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.270751 - Iter 028 / 029, Loss: 0.050436 * Train accuracy / confusion: 93.53% / [[333, 29], [31, 535]], * Val accuracy / confusion: 68.31% / [[124, 106], [81, 279]] ------------------------------ Epoch 295 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.085420 - Iter 028 / 029, Loss: 0.103432 * Train accuracy / confusion: 93.64% / [[334, 27], [32, 535]], * Val accuracy / confusion: 70.68% / [[151, 79], [94, 266]] ------------------------------ Epoch 296 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.162707 - Iter 028 / 029, Loss: 0.167908 * Train accuracy / confusion: 94.18% / [[342, 21], [33, 532]], * Val accuracy / confusion: 70.68% / [[146, 84], [89, 271]] ------------------------------ Epoch 297 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.195168 - Iter 028 / 029, Loss: 0.171942 * Train accuracy / confusion: 94.40% / [[332, 25], [27, 544]], * Val accuracy / confusion: 68.98% / [[135, 95], [88, 272]] ------------------------------ Epoch 298 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.173031 - Iter 028 / 029, Loss: 0.118620 * Train accuracy / confusion: 94.72% / [[337, 23], [26, 542]], * Val accuracy / confusion: 67.80% / [[121, 109], [81, 279]] ------------------------------ Epoch 299 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.071360 - Iter 028 / 029, Loss: 0.224990 * Train accuracy / confusion: 95.80% / [[347, 17], [22, 542]], * Val accuracy / confusion: 69.83% / [[140, 90], [88, 272]] ------------------------------ Epoch 300 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.131423 - Iter 028 / 029, Loss: 0.200167 * Train accuracy / confusion: 95.15% / [[342, 21], [24, 541]], * Val accuracy / confusion: 71.19% / [[133, 97], [73, 287]] ------------------------------ Epoch 301 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.157800 - Iter 028 / 029, Loss: 0.105528 * Train accuracy / confusion: 95.58% / [[347, 15], [26, 540]], * Val accuracy / confusion: 70.51% / [[136, 94], [80, 280]] ------------------------------ Epoch 302 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.122555 - Iter 028 / 029, Loss: 0.076210 * Train accuracy / confusion: 94.72% / [[332, 28], [21, 547]], * Val accuracy / confusion: 67.97% / [[143, 87], [102, 258]] ------------------------------ Epoch 303 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.256020 - Iter 028 / 029, Loss: 0.143792 * Train accuracy / confusion: 95.15% / [[343, 19], [26, 540]], * Val accuracy / confusion: 70.17% / [[132, 98], [78, 282]] ------------------------------ Epoch 304 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.048430 - Iter 028 / 029, Loss: 0.099909 * Train accuracy / confusion: 96.12% / [[349, 15], [21, 543]], * Val accuracy / confusion: 69.66% / [[139, 91], [88, 272]] ------------------------------ Epoch 305 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.109072 - Iter 028 / 029, Loss: 0.067421 * Train accuracy / confusion: 95.37% / [[341, 21], [22, 544]], * Val accuracy / confusion: 68.47% / [[130, 100], [86, 274]] ------------------------------ Epoch 306 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.175473 - Iter 028 / 029, Loss: 0.113788 * Train accuracy / confusion: 94.29% / [[335, 27], [26, 540]], * Val accuracy / confusion: 67.80% / [[129, 101], [89, 271]] ------------------------------ Epoch 307 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.236776 - Iter 028 / 029, Loss: 0.223446 * Train accuracy / confusion: 93.97% / [[339, 24], [32, 533]], * Val accuracy / confusion: 67.97% / [[126, 104], [85, 275]] ------------------------------ Epoch 308 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.086244 - Iter 028 / 029, Loss: 0.118402 * Train accuracy / confusion: 96.23% / [[343, 15], [20, 550]], * Val accuracy / confusion: 68.64% / [[121, 109], [76, 284]] ------------------------------ Epoch 309 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.097376 - Iter 028 / 029, Loss: 0.066914 * Train accuracy / confusion: 94.72% / [[342, 20], [29, 537]], * Val accuracy / confusion: 68.47% / [[135, 95], [91, 269]] ------------------------------ Epoch 310 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.079346 - Iter 028 / 029, Loss: 0.110280 * Train accuracy / confusion: 93.97% / [[336, 26], [30, 536]], * Val accuracy / confusion: 68.81% / [[138, 92], [92, 268]] ------------------------------ Epoch 311 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.313493 - Iter 028 / 029, Loss: 0.078328 * Train accuracy / confusion: 94.94% / [[336, 24], [23, 545]], * Val accuracy / confusion: 67.12% / [[124, 106], [88, 272]] ------------------------------ Epoch 312 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.068824 - Iter 028 / 029, Loss: 0.129002 * Train accuracy / confusion: 94.29% / [[338, 26], [27, 537]], * Val accuracy / confusion: 67.46% / [[138, 92], [100, 260]] ------------------------------ Epoch 313 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.172609 - Iter 028 / 029, Loss: 0.180219 * Train accuracy / confusion: 93.86% / [[334, 29], [28, 537]], * Val accuracy / confusion: 67.12% / [[149, 81], [113, 247]] ------------------------------ Epoch 314 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.175417 - Iter 028 / 029, Loss: 0.178459 * Train accuracy / confusion: 94.50% / [[332, 27], [24, 545]], * Val accuracy / confusion: 66.95% / [[120, 110], [85, 275]] ------------------------------ Epoch 315 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.170634 - Iter 028 / 029, Loss: 0.077409 * Train accuracy / confusion: 93.97% / [[332, 28], [28, 540]], * Val accuracy / confusion: 68.98% / [[142, 88], [95, 265]] ------------------------------ Epoch 316 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.169219 - Iter 028 / 029, Loss: 0.098813 * Train accuracy / confusion: 94.94% / [[338, 20], [27, 543]], * Val accuracy / confusion: 68.64% / [[118, 112], [73, 287]] ------------------------------ Epoch 317 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.145134 - Iter 028 / 029, Loss: 0.090209 * Train accuracy / confusion: 94.18% / [[338, 28], [26, 536]], * Val accuracy / confusion: 66.61% / [[129, 101], [96, 264]] ------------------------------ Epoch 318 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.058477 - Iter 028 / 029, Loss: 0.051637 * Train accuracy / confusion: 94.83% / [[350, 13], [35, 530]], * Val accuracy / confusion: 70.85% / [[141, 89], [83, 277]] ------------------------------ Epoch 319 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.271114 - Iter 028 / 029, Loss: 0.177126 * Train accuracy / confusion: 94.07% / [[330, 30], [25, 543]], * Val accuracy / confusion: 69.32% / [[145, 85], [96, 264]] ------------------------------ Epoch 320 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.133740 - Iter 028 / 029, Loss: 0.242708 * Train accuracy / confusion: 94.18% / [[334, 26], [28, 540]], * Val accuracy / confusion: 68.14% / [[135, 95], [93, 267]] ------------------------------ Epoch 321 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.036527 - Iter 028 / 029, Loss: 0.158961 * Train accuracy / confusion: 94.40% / [[333, 25], [27, 543]], * Val accuracy / confusion: 67.80% / [[140, 90], [100, 260]] ------------------------------ Epoch 322 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.070658 - Iter 028 / 029, Loss: 0.189199 * Train accuracy / confusion: 95.26% / [[344, 22], [22, 540]], * Val accuracy / confusion: 69.66% / [[128, 102], [77, 283]] ------------------------------ Epoch 323 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.087127 - Iter 028 / 029, Loss: 0.154455 * Train accuracy / confusion: 95.26% / [[344, 19], [25, 540]], * Val accuracy / confusion: 67.46% / [[131, 99], [93, 267]] ------------------------------ Epoch 324 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.148468 - Iter 028 / 029, Loss: 0.142296 * Train accuracy / confusion: 94.72% / [[339, 26], [23, 540]], * Val accuracy / confusion: 65.93% / [[119, 111], [90, 270]] ------------------------------ Epoch 325 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.160859 - Iter 028 / 029, Loss: 0.304181 * Train accuracy / confusion: 93.86% / [[336, 28], [29, 535]], * Val accuracy / confusion: 67.63% / [[138, 92], [99, 261]] ------------------------------ Epoch 326 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.046102 - Iter 028 / 029, Loss: 0.182175 * Train accuracy / confusion: 95.15% / [[340, 25], [20, 543]], * Val accuracy / confusion: 68.98% / [[121, 109], [74, 286]] ------------------------------ Epoch 327 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.170250 - Iter 028 / 029, Loss: 0.063622 * Train accuracy / confusion: 94.40% / [[338, 26], [26, 538]], * Val accuracy / confusion: 68.31% / [[136, 94], [93, 267]] ------------------------------ Epoch 328 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.066311 - Iter 028 / 029, Loss: 0.125233 * Train accuracy / confusion: 94.94% / [[344, 18], [29, 537]], * Val accuracy / confusion: 68.14% / [[137, 93], [95, 265]] ------------------------------ Epoch 329 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.135147 - Iter 028 / 029, Loss: 0.096664 * Train accuracy / confusion: 96.12% / [[345, 20], [16, 547]], * Val accuracy / confusion: 65.25% / [[119, 111], [94, 266]] ------------------------------ Epoch 330 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.067254 - Iter 028 / 029, Loss: 0.150719 * Train accuracy / confusion: 95.58% / [[339, 20], [21, 548]], * Val accuracy / confusion: 66.27% / [[135, 95], [104, 256]] ------------------------------ Epoch 331 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.102575 - Iter 028 / 029, Loss: 0.073127 * Train accuracy / confusion: 94.94% / [[342, 22], [25, 539]], * Val accuracy / confusion: 68.47% / [[141, 89], [97, 263]] ------------------------------ Epoch 332 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.121672 - Iter 028 / 029, Loss: 0.183077 * Train accuracy / confusion: 94.83% / [[335, 26], [22, 545]], * Val accuracy / confusion: 68.14% / [[137, 93], [95, 265]] ------------------------------ Epoch 333 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.169130 - Iter 028 / 029, Loss: 0.221433 * Train accuracy / confusion: 94.83% / [[346, 19], [29, 534]], * Val accuracy / confusion: 68.81% / [[137, 93], [91, 269]] ------------------------------ Epoch 334 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.185612 - Iter 028 / 029, Loss: 0.160654 * Train accuracy / confusion: 94.40% / [[333, 28], [24, 543]], * Val accuracy / confusion: 67.97% / [[142, 88], [101, 259]] ------------------------------ Epoch 335 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.073506 - Iter 028 / 029, Loss: 0.121337 * Train accuracy / confusion: 95.15% / [[345, 19], [26, 538]], * Val accuracy / confusion: 65.76% / [[110, 120], [82, 278]] ------------------------------ Epoch 336 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.058193 - Iter 028 / 029, Loss: 0.132189 * Train accuracy / confusion: 95.47% / [[338, 19], [23, 548]], * Val accuracy / confusion: 66.95% / [[130, 100], [95, 265]] ------------------------------ Epoch 337 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.105728 - Iter 028 / 029, Loss: 0.219411 * Train accuracy / confusion: 94.50% / [[336, 26], [25, 541]], * Val accuracy / confusion: 67.46% / [[142, 88], [104, 256]] ------------------------------ Epoch 338 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.098872 - Iter 028 / 029, Loss: 0.074654 * Train accuracy / confusion: 94.40% / [[338, 25], [27, 538]], * Val accuracy / confusion: 68.81% / [[135, 95], [89, 271]] ------------------------------ Epoch 339 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.120200 - Iter 028 / 029, Loss: 0.108809 * Train accuracy / confusion: 93.75% / [[335, 29], [29, 535]], * Val accuracy / confusion: 70.00% / [[129, 101], [76, 284]] ------------------------------ Epoch 340 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.211037 - Iter 028 / 029, Loss: 0.137453 * Train accuracy / confusion: 95.04% / [[339, 23], [23, 543]], * Val accuracy / confusion: 67.80% / [[136, 94], [96, 264]] ------------------------------ Epoch 341 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.133986 - Iter 028 / 029, Loss: 0.058359 * Train accuracy / confusion: 96.34% / [[347, 15], [19, 547]], * Val accuracy / confusion: 68.31% / [[143, 87], [100, 260]] ------------------------------ Epoch 342 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.107019 - Iter 028 / 029, Loss: 0.077239 * Train accuracy / confusion: 95.58% / [[353, 14], [27, 534]], * Val accuracy / confusion: 68.14% / [[117, 113], [75, 285]] ------------------------------ Epoch 343 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.093837 - Iter 028 / 029, Loss: 0.068568 * Train accuracy / confusion: 95.47% / [[335, 25], [17, 551]], * Val accuracy / confusion: 66.61% / [[130, 100], [97, 263]] ------------------------------ Epoch 344 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.108102 - Iter 028 / 029, Loss: 0.080271 * Train accuracy / confusion: 95.58% / [[342, 18], [23, 545]], * Val accuracy / confusion: 67.80% / [[141, 89], [101, 259]] ------------------------------ Epoch 345 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.059575 - Iter 028 / 029, Loss: 0.096957 * Train accuracy / confusion: 95.26% / [[342, 21], [23, 542]], * Val accuracy / confusion: 67.46% / [[149, 81], [111, 249]] ------------------------------ Epoch 346 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.046525 - Iter 028 / 029, Loss: 0.050251 * Train accuracy / confusion: 96.12% / [[345, 19], [17, 547]], * Val accuracy / confusion: 66.95% / [[136, 94], [101, 259]] ------------------------------ Epoch 347 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.056685 - Iter 028 / 029, Loss: 0.186959 * Train accuracy / confusion: 95.58% / [[346, 17], [24, 541]], * Val accuracy / confusion: 67.29% / [[128, 102], [91, 269]] ------------------------------ Epoch 348 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.235084 - Iter 028 / 029, Loss: 0.054753 * Train accuracy / confusion: 94.61% / [[338, 24], [26, 540]], * Val accuracy / confusion: 71.02% / [[147, 83], [88, 272]] ------------------------------ Epoch 349 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.175035 - Iter 028 / 029, Loss: 0.082441 * Train accuracy / confusion: 94.07% / [[338, 26], [29, 535]], * Val accuracy / confusion: 67.29% / [[139, 91], [102, 258]] ------------------------------ Epoch 350 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.202007 - Iter 028 / 029, Loss: 0.134148 * Train accuracy / confusion: 95.47% / [[348, 15], [27, 538]], * Val accuracy / confusion: 66.78% / [[131, 99], [97, 263]] ------------------------------ Epoch 351 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.190650 - Iter 028 / 029, Loss: 0.183202 * Train accuracy / confusion: 96.23% / [[343, 19], [16, 550]], * Val accuracy / confusion: 68.14% / [[140, 90], [98, 262]] ------------------------------ Epoch 352 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.065578 - Iter 028 / 029, Loss: 0.065612 * Train accuracy / confusion: 96.12% / [[345, 17], [19, 547]], * Val accuracy / confusion: 66.78% / [[130, 100], [96, 264]] ------------------------------ Epoch 353 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.106928 - Iter 028 / 029, Loss: 0.167719 * Train accuracy / confusion: 93.97% / [[337, 24], [32, 535]], * Val accuracy / confusion: 66.61% / [[126, 104], [93, 267]] ------------------------------ Epoch 354 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.097796 - Iter 028 / 029, Loss: 0.080782 * Train accuracy / confusion: 94.72% / [[342, 22], [27, 537]], * Val accuracy / confusion: 70.68% / [[141, 89], [84, 276]] ------------------------------ Epoch 355 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.196650 - Iter 028 / 029, Loss: 0.200540 * Train accuracy / confusion: 94.40% / [[336, 26], [26, 540]], * Val accuracy / confusion: 66.78% / [[123, 107], [89, 271]] ------------------------------ Epoch 356 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.256326 - Iter 028 / 029, Loss: 0.121626 * Train accuracy / confusion: 94.29% / [[345, 17], [36, 530]], * Val accuracy / confusion: 69.32% / [[136, 94], [87, 273]] ------------------------------ Epoch 357 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.064684 - Iter 028 / 029, Loss: 0.054569 * Train accuracy / confusion: 95.69% / [[344, 19], [21, 544]], * Val accuracy / confusion: 65.93% / [[123, 107], [94, 266]] ------------------------------ Epoch 358 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.057747 - Iter 028 / 029, Loss: 0.292493 * Train accuracy / confusion: 93.64% / [[335, 26], [33, 534]], * Val accuracy / confusion: 66.78% / [[133, 97], [99, 261]] ------------------------------ Epoch 359 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.101065 - Iter 028 / 029, Loss: 0.185591 * Train accuracy / confusion: 94.72% / [[340, 24], [25, 539]], * Val accuracy / confusion: 68.31% / [[122, 108], [79, 281]] ------------------------------ Epoch 360 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.169358 - Iter 028 / 029, Loss: 0.072201 * Train accuracy / confusion: 96.66% / [[346, 15], [16, 551]], * Val accuracy / confusion: 67.46% / [[141, 89], [103, 257]] ------------------------------ Epoch 361 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.118681 - Iter 028 / 029, Loss: 0.059454 * Train accuracy / confusion: 95.91% / [[341, 19], [19, 549]], * Val accuracy / confusion: 65.93% / [[107, 123], [78, 282]] ------------------------------ Epoch 362 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.135931 - Iter 028 / 029, Loss: 0.131474 * Train accuracy / confusion: 95.37% / [[341, 21], [22, 544]], * Val accuracy / confusion: 68.98% / [[136, 94], [89, 271]] ------------------------------ Epoch 363 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.091462 - Iter 028 / 029, Loss: 0.080713 * Train accuracy / confusion: 96.44% / [[344, 15], [18, 551]], * Val accuracy / confusion: 69.15% / [[146, 84], [98, 262]] ------------------------------ Epoch 364 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.165153 - Iter 028 / 029, Loss: 0.344864 * Train accuracy / confusion: 93.86% / [[339, 27], [30, 532]], * Val accuracy / confusion: 68.31% / [[127, 103], [84, 276]] ------------------------------ Epoch 365 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.044118 - Iter 028 / 029, Loss: 0.159186 * Train accuracy / confusion: 95.15% / [[341, 21], [24, 542]], * Val accuracy / confusion: 66.78% / [[118, 112], [84, 276]] ------------------------------ Epoch 366 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.277915 - Iter 028 / 029, Loss: 0.136028 * Train accuracy / confusion: 95.80% / [[344, 16], [23, 545]], * Val accuracy / confusion: 66.10% / [[124, 106], [94, 266]] ------------------------------ Epoch 367 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.105249 - Iter 028 / 029, Loss: 0.122580 * Train accuracy / confusion: 95.15% / [[344, 19], [26, 539]], * Val accuracy / confusion: 68.31% / [[147, 83], [104, 256]] ------------------------------ Epoch 368 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.152438 - Iter 028 / 029, Loss: 0.152309 * Train accuracy / confusion: 95.26% / [[341, 23], [21, 543]], * Val accuracy / confusion: 69.32% / [[123, 107], [74, 286]] ------------------------------ Epoch 369 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.070277 - Iter 028 / 029, Loss: 0.066638 * Train accuracy / confusion: 95.47% / [[345, 19], [23, 541]], * Val accuracy / confusion: 68.47% / [[131, 99], [87, 273]] ------------------------------ Epoch 370 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.060398 - Iter 028 / 029, Loss: 0.046534 * Train accuracy / confusion: 96.01% / [[348, 16], [21, 543]], * Val accuracy / confusion: 68.47% / [[138, 92], [94, 266]] ------------------------------ Epoch 371 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.084089 - Iter 028 / 029, Loss: 0.050690 * Train accuracy / confusion: 95.80% / [[341, 23], [16, 548]], * Val accuracy / confusion: 69.15% / [[138, 92], [90, 270]] ------------------------------ Epoch 372 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.035847 - Iter 028 / 029, Loss: 0.138778 * Train accuracy / confusion: 95.26% / [[339, 23], [21, 545]], * Val accuracy / confusion: 68.14% / [[134, 96], [92, 268]] ------------------------------ Epoch 373 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.164676 - Iter 028 / 029, Loss: 0.115134 * Train accuracy / confusion: 95.58% / [[339, 21], [20, 548]], * Val accuracy / confusion: 68.81% / [[126, 104], [80, 280]] ------------------------------ Epoch 374 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.130024 - Iter 028 / 029, Loss: 0.098265 * Train accuracy / confusion: 95.91% / [[347, 18], [20, 543]], * Val accuracy / confusion: 72.20% / [[144, 86], [78, 282]] ------------------------------ Epoch 375 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.097255 - Iter 028 / 029, Loss: 0.142064 * Train accuracy / confusion: 95.15% / [[339, 22], [23, 544]], * Val accuracy / confusion: 68.47% / [[122, 108], [78, 282]] ------------------------------ Epoch 376 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.091294 - Iter 028 / 029, Loss: 0.123829 * Train accuracy / confusion: 94.83% / [[342, 20], [28, 538]], * Val accuracy / confusion: 69.15% / [[137, 93], [89, 271]] ------------------------------ Epoch 377 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.095090 - Iter 028 / 029, Loss: 0.391271 * Train accuracy / confusion: 96.23% / [[343, 17], [18, 550]], * Val accuracy / confusion: 68.14% / [[125, 105], [83, 277]] ------------------------------ Epoch 378 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.068102 - Iter 028 / 029, Loss: 0.046803 * Train accuracy / confusion: 95.91% / [[337, 22], [16, 553]], * Val accuracy / confusion: 70.00% / [[129, 101], [76, 284]] ------------------------------ Epoch 379 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.097318 - Iter 028 / 029, Loss: 0.089158 * Train accuracy / confusion: 96.01% / [[341, 19], [18, 550]], * Val accuracy / confusion: 68.14% / [[127, 103], [85, 275]] ------------------------------ Epoch 380 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.134736 - Iter 028 / 029, Loss: 0.135595 * Train accuracy / confusion: 95.58% / [[348, 14], [27, 539]], * Val accuracy / confusion: 68.47% / [[135, 95], [91, 269]] ------------------------------ Epoch 381 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.215593 - Iter 028 / 029, Loss: 0.076880 * Train accuracy / confusion: 94.72% / [[344, 18], [31, 535]], * Val accuracy / confusion: 70.51% / [[139, 91], [83, 277]] ------------------------------ Epoch 382 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.111896 - Iter 028 / 029, Loss: 0.128103 * Train accuracy / confusion: 95.80% / [[342, 19], [20, 547]], * Val accuracy / confusion: 67.29% / [[130, 100], [93, 267]] ------------------------------ Epoch 383 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.296732 - Iter 028 / 029, Loss: 0.267793 * Train accuracy / confusion: 95.47% / [[342, 20], [22, 544]], * Val accuracy / confusion: 69.32% / [[150, 80], [101, 259]] ------------------------------ Epoch 384 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.147108 - Iter 028 / 029, Loss: 0.125893 * Train accuracy / confusion: 95.04% / [[340, 19], [27, 542]], * Val accuracy / confusion: 69.49% / [[128, 102], [78, 282]] ------------------------------ Epoch 385 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.149432 - Iter 028 / 029, Loss: 0.207769 * Train accuracy / confusion: 94.61% / [[339, 19], [31, 539]], * Val accuracy / confusion: 69.32% / [[141, 89], [92, 268]] ------------------------------ Epoch 386 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.190896 - Iter 028 / 029, Loss: 0.176521 * Train accuracy / confusion: 94.72% / [[335, 27], [22, 544]], * Val accuracy / confusion: 68.98% / [[136, 94], [89, 271]] ------------------------------ Epoch 387 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.038842 - Iter 028 / 029, Loss: 0.096183 * Train accuracy / confusion: 95.26% / [[344, 18], [26, 540]], * Val accuracy / confusion: 69.32% / [[134, 96], [85, 275]] ------------------------------ Epoch 388 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.151997 - Iter 028 / 029, Loss: 0.158945 * Train accuracy / confusion: 95.80% / [[342, 19], [20, 547]], * Val accuracy / confusion: 68.47% / [[136, 94], [92, 268]] ------------------------------ Epoch 389 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.054244 - Iter 028 / 029, Loss: 0.110984 * Train accuracy / confusion: 95.47% / [[345, 20], [22, 541]], * Val accuracy / confusion: 66.95% / [[130, 100], [95, 265]] ------------------------------ Epoch 390 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.063842 - Iter 028 / 029, Loss: 0.089608 * Train accuracy / confusion: 95.15% / [[337, 23], [22, 546]], * Val accuracy / confusion: 66.95% / [[130, 100], [95, 265]] ------------------------------ Epoch 391 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.074373 - Iter 028 / 029, Loss: 0.108102 * Train accuracy / confusion: 96.01% / [[345, 15], [22, 546]], * Val accuracy / confusion: 69.32% / [[150, 80], [101, 259]] ------------------------------ Epoch 392 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.077245 - Iter 028 / 029, Loss: 0.108548 * Train accuracy / confusion: 96.34% / [[347, 15], [19, 547]], * Val accuracy / confusion: 68.14% / [[132, 98], [90, 270]] ------------------------------ Epoch 393 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.124858 - Iter 028 / 029, Loss: 0.194335 * Train accuracy / confusion: 95.80% / [[341, 22], [17, 548]], * Val accuracy / confusion: 67.12% / [[134, 96], [98, 262]] ------------------------------ Epoch 394 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.135216 - Iter 028 / 029, Loss: 0.094540 * Train accuracy / confusion: 95.04% / [[339, 25], [21, 543]], * Val accuracy / confusion: 68.98% / [[135, 95], [88, 272]] ------------------------------ Epoch 395 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.121714 - Iter 028 / 029, Loss: 0.167349 * Train accuracy / confusion: 93.97% / [[334, 27], [29, 538]], * Val accuracy / confusion: 70.68% / [[156, 74], [99, 261]] ------------------------------ Epoch 396 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.087944 - Iter 028 / 029, Loss: 0.062862 * Train accuracy / confusion: 95.15% / [[341, 23], [22, 542]], * Val accuracy / confusion: 68.81% / [[123, 107], [77, 283]] ------------------------------ Epoch 397 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.117390 - Iter 028 / 029, Loss: 0.278798 * Train accuracy / confusion: 95.15% / [[342, 23], [22, 541]], * Val accuracy / confusion: 67.97% / [[135, 95], [94, 266]] ------------------------------ Epoch 398 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.060216 - Iter 028 / 029, Loss: 0.126694 * Train accuracy / confusion: 95.47% / [[342, 17], [25, 544]], * Val accuracy / confusion: 68.81% / [[130, 100], [84, 276]] ------------------------------ Epoch 399 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.045156 - Iter 028 / 029, Loss: 0.279046 * Train accuracy / confusion: 95.80% / [[346, 15], [24, 543]], * Val accuracy / confusion: 67.97% / [[135, 95], [94, 266]] ------------------------------ Epoch 400 / 500, Learning rate: 1.49e-05 ------------------------------ - Iter 014 / 029, Loss: 0.132515 - Iter 028 / 029, Loss: 0.138269 * Train accuracy / confusion: 95.91% / [[342, 18], [20, 548]], * Val accuracy / confusion: 68.98% / [[143, 87], [96, 264]] ------------------------------ Epoch 401 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.237513 - Iter 028 / 029, Loss: 0.055975 * Train accuracy / confusion: 95.69% / [[347, 15], [25, 541]], * Val accuracy / confusion: 68.47% / [[141, 89], [97, 263]] ------------------------------ Epoch 402 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.083412 - Iter 028 / 029, Loss: 0.301790 * Train accuracy / confusion: 95.37% / [[340, 21], [22, 545]], * Val accuracy / confusion: 65.76% / [[130, 100], [102, 258]] ------------------------------ Epoch 403 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.096354 - Iter 028 / 029, Loss: 0.121829 * Train accuracy / confusion: 95.80% / [[342, 18], [21, 547]], * Val accuracy / confusion: 67.63% / [[127, 103], [88, 272]] ------------------------------ Epoch 404 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.131755 - Iter 028 / 029, Loss: 0.079270 * Train accuracy / confusion: 95.47% / [[341, 21], [21, 545]], * Val accuracy / confusion: 68.31% / [[140, 90], [97, 263]] ------------------------------ Epoch 405 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.536256 - Iter 028 / 029, Loss: 0.075495 * Train accuracy / confusion: 95.26% / [[337, 23], [21, 547]], * Val accuracy / confusion: 69.15% / [[135, 95], [87, 273]] ------------------------------ Epoch 406 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.033668 - Iter 028 / 029, Loss: 0.113685 * Train accuracy / confusion: 95.58% / [[349, 14], [27, 538]], * Val accuracy / confusion: 70.34% / [[148, 82], [93, 267]] ------------------------------ Epoch 407 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.227985 - Iter 028 / 029, Loss: 0.104173 * Train accuracy / confusion: 95.58% / [[343, 21], [20, 544]], * Val accuracy / confusion: 70.00% / [[139, 91], [86, 274]] ------------------------------ Epoch 408 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.124025 - Iter 028 / 029, Loss: 0.102646 * Train accuracy / confusion: 95.69% / [[341, 20], [20, 547]], * Val accuracy / confusion: 69.83% / [[137, 93], [85, 275]] ------------------------------ Epoch 409 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.185316 - Iter 028 / 029, Loss: 0.047892 * Train accuracy / confusion: 94.94% / [[340, 20], [27, 541]], * Val accuracy / confusion: 66.61% / [[132, 98], [99, 261]] ------------------------------ Epoch 410 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.023774 - Iter 028 / 029, Loss: 0.135025 * Train accuracy / confusion: 96.01% / [[346, 17], [20, 545]], * Val accuracy / confusion: 68.14% / [[137, 93], [95, 265]] ------------------------------ Epoch 411 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.200634 - Iter 028 / 029, Loss: 0.122579 * Train accuracy / confusion: 96.23% / [[345, 19], [16, 548]], * Val accuracy / confusion: 68.81% / [[135, 95], [89, 271]] ------------------------------ Epoch 412 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.168961 - Iter 028 / 029, Loss: 0.082464 * Train accuracy / confusion: 95.80% / [[350, 15], [24, 539]], * Val accuracy / confusion: 67.29% / [[124, 106], [87, 273]] ------------------------------ Epoch 413 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.114673 - Iter 028 / 029, Loss: 0.145782 * Train accuracy / confusion: 95.15% / [[340, 21], [24, 543]], * Val accuracy / confusion: 68.31% / [[138, 92], [95, 265]] ------------------------------ Epoch 414 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.075066 - Iter 028 / 029, Loss: 0.182735 * Train accuracy / confusion: 96.44% / [[344, 18], [15, 551]], * Val accuracy / confusion: 65.42% / [[120, 110], [94, 266]] ------------------------------ Epoch 415 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.043609 - Iter 028 / 029, Loss: 0.131782 * Train accuracy / confusion: 95.69% / [[343, 19], [21, 545]], * Val accuracy / confusion: 69.66% / [[145, 85], [94, 266]] ------------------------------ Epoch 416 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.226917 - Iter 028 / 029, Loss: 0.149855 * Train accuracy / confusion: 96.23% / [[345, 16], [19, 548]], * Val accuracy / confusion: 71.02% / [[146, 84], [87, 273]] ------------------------------ Epoch 417 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.096994 - Iter 028 / 029, Loss: 0.076587 * Train accuracy / confusion: 96.12% / [[350, 14], [22, 542]], * Val accuracy / confusion: 69.15% / [[129, 101], [81, 279]] ------------------------------ Epoch 418 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.121044 - Iter 028 / 029, Loss: 0.077279 * Train accuracy / confusion: 97.09% / [[348, 12], [15, 553]], * Val accuracy / confusion: 68.14% / [[134, 96], [92, 268]] ------------------------------ Epoch 419 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.229824 - Iter 028 / 029, Loss: 0.035667 * Train accuracy / confusion: 95.58% / [[343, 19], [22, 544]], * Val accuracy / confusion: 68.64% / [[137, 93], [92, 268]] ------------------------------ Epoch 420 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.135769 - Iter 028 / 029, Loss: 0.036767 * Train accuracy / confusion: 96.01% / [[346, 19], [18, 545]], * Val accuracy / confusion: 67.97% / [[127, 103], [86, 274]] ------------------------------ Epoch 421 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.106702 - Iter 028 / 029, Loss: 0.067549 * Train accuracy / confusion: 96.77% / [[348, 16], [14, 550]], * Val accuracy / confusion: 68.64% / [[132, 98], [87, 273]] ------------------------------ Epoch 422 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.077343 - Iter 028 / 029, Loss: 0.049381 * Train accuracy / confusion: 96.23% / [[346, 18], [17, 547]], * Val accuracy / confusion: 69.66% / [[136, 94], [85, 275]] ------------------------------ Epoch 423 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.078177 - Iter 028 / 029, Loss: 0.047584 * Train accuracy / confusion: 95.80% / [[345, 18], [21, 544]], * Val accuracy / confusion: 69.49% / [[140, 90], [90, 270]] ------------------------------ Epoch 424 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.108157 - Iter 028 / 029, Loss: 0.058163 * Train accuracy / confusion: 96.88% / [[353, 11], [18, 546]], * Val accuracy / confusion: 68.47% / [[135, 95], [91, 269]] ------------------------------ Epoch 425 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.069349 - Iter 028 / 029, Loss: 0.142515 * Train accuracy / confusion: 96.12% / [[345, 18], [18, 547]], * Val accuracy / confusion: 69.15% / [[140, 90], [92, 268]] ------------------------------ Epoch 426 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.088471 - Iter 028 / 029, Loss: 0.135875 * Train accuracy / confusion: 96.66% / [[346, 14], [17, 551]], * Val accuracy / confusion: 68.64% / [[138, 92], [93, 267]] ------------------------------ Epoch 427 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.076951 - Iter 028 / 029, Loss: 0.150752 * Train accuracy / confusion: 95.91% / [[340, 21], [17, 550]], * Val accuracy / confusion: 69.49% / [[138, 92], [88, 272]] ------------------------------ Epoch 428 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.079060 - Iter 028 / 029, Loss: 0.050776 * Train accuracy / confusion: 95.80% / [[346, 17], [22, 543]], * Val accuracy / confusion: 67.12% / [[130, 100], [94, 266]] ------------------------------ Epoch 429 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.114599 - Iter 028 / 029, Loss: 0.041878 * Train accuracy / confusion: 96.12% / [[349, 17], [19, 543]], * Val accuracy / confusion: 67.97% / [[132, 98], [91, 269]] ------------------------------ Epoch 430 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.057967 - Iter 028 / 029, Loss: 0.086929 * Train accuracy / confusion: 96.44% / [[351, 14], [19, 544]], * Val accuracy / confusion: 67.80% / [[130, 100], [90, 270]] ------------------------------ Epoch 431 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.125219 - Iter 028 / 029, Loss: 0.105233 * Train accuracy / confusion: 95.26% / [[346, 19], [25, 538]], * Val accuracy / confusion: 68.64% / [[138, 92], [93, 267]] ------------------------------ Epoch 432 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.065211 - Iter 028 / 029, Loss: 0.255204 * Train accuracy / confusion: 95.91% / [[349, 13], [25, 541]], * Val accuracy / confusion: 66.10% / [[122, 108], [92, 268]] ------------------------------ Epoch 433 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.135067 - Iter 028 / 029, Loss: 0.121208 * Train accuracy / confusion: 94.94% / [[342, 23], [24, 539]], * Val accuracy / confusion: 68.81% / [[130, 100], [84, 276]] ------------------------------ Epoch 434 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.028629 - Iter 028 / 029, Loss: 0.076290 * Train accuracy / confusion: 96.23% / [[347, 17], [18, 546]], * Val accuracy / confusion: 69.66% / [[135, 95], [84, 276]] ------------------------------ Epoch 435 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.046568 - Iter 028 / 029, Loss: 0.189631 * Train accuracy / confusion: 95.58% / [[347, 16], [25, 540]], * Val accuracy / confusion: 67.12% / [[122, 108], [86, 274]] ------------------------------ Epoch 436 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.158209 - Iter 028 / 029, Loss: 0.047177 * Train accuracy / confusion: 97.52% / [[350, 12], [11, 555]], * Val accuracy / confusion: 67.63% / [[128, 102], [89, 271]] ------------------------------ Epoch 437 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.281356 - Iter 028 / 029, Loss: 0.094443 * Train accuracy / confusion: 96.23% / [[348, 16], [19, 545]], * Val accuracy / confusion: 69.83% / [[134, 96], [82, 278]] ------------------------------ Epoch 438 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.048986 - Iter 028 / 029, Loss: 0.086678 * Train accuracy / confusion: 95.91% / [[336, 21], [17, 554]], * Val accuracy / confusion: 66.95% / [[133, 97], [98, 262]] ------------------------------ Epoch 439 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.053258 - Iter 028 / 029, Loss: 0.031636 * Train accuracy / confusion: 97.31% / [[348, 11], [14, 555]], * Val accuracy / confusion: 67.80% / [[133, 97], [93, 267]] ------------------------------ Epoch 440 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.161576 - Iter 028 / 029, Loss: 0.107981 * Train accuracy / confusion: 95.69% / [[343, 18], [22, 545]], * Val accuracy / confusion: 68.47% / [[132, 98], [88, 272]] ------------------------------ Epoch 441 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.072994 - Iter 028 / 029, Loss: 0.182703 * Train accuracy / confusion: 96.01% / [[341, 23], [14, 550]], * Val accuracy / confusion: 70.17% / [[143, 87], [89, 271]] ------------------------------ Epoch 442 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.106194 - Iter 028 / 029, Loss: 0.050003 * Train accuracy / confusion: 97.52% / [[353, 11], [12, 552]], * Val accuracy / confusion: 67.63% / [[132, 98], [93, 267]] ------------------------------ Epoch 443 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.030229 - Iter 028 / 029, Loss: 0.141357 * Train accuracy / confusion: 95.47% / [[339, 22], [20, 547]], * Val accuracy / confusion: 69.66% / [[130, 100], [79, 281]] ------------------------------ Epoch 444 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.132710 - Iter 028 / 029, Loss: 0.093640 * Train accuracy / confusion: 95.58% / [[346, 18], [23, 541]], * Val accuracy / confusion: 69.15% / [[140, 90], [92, 268]] ------------------------------ Epoch 445 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.218216 - Iter 028 / 029, Loss: 0.135777 * Train accuracy / confusion: 95.47% / [[343, 19], [23, 543]], * Val accuracy / confusion: 67.46% / [[142, 88], [104, 256]] ------------------------------ Epoch 446 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.086350 - Iter 028 / 029, Loss: 0.146090 * Train accuracy / confusion: 96.55% / [[345, 22], [10, 551]], * Val accuracy / confusion: 68.64% / [[134, 96], [89, 271]] ------------------------------ Epoch 447 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.134305 - Iter 028 / 029, Loss: 0.064454 * Train accuracy / confusion: 96.01% / [[346, 17], [20, 545]], * Val accuracy / confusion: 66.95% / [[140, 90], [105, 255]] ------------------------------ Epoch 448 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.053172 - Iter 028 / 029, Loss: 0.122888 * Train accuracy / confusion: 96.34% / [[348, 16], [18, 546]], * Val accuracy / confusion: 70.51% / [[132, 98], [76, 284]] ------------------------------ Epoch 449 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.054928 - Iter 028 / 029, Loss: 0.076952 * Train accuracy / confusion: 96.66% / [[348, 15], [16, 549]], * Val accuracy / confusion: 68.31% / [[132, 98], [89, 271]] ------------------------------ Epoch 450 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.115848 - Iter 028 / 029, Loss: 0.039075 * Train accuracy / confusion: 95.58% / [[346, 18], [23, 541]], * Val accuracy / confusion: 69.49% / [[141, 89], [91, 269]] ------------------------------ Epoch 451 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.051524 - Iter 028 / 029, Loss: 0.067687 * Train accuracy / confusion: 96.55% / [[342, 18], [14, 554]], * Val accuracy / confusion: 66.78% / [[125, 105], [91, 269]] ------------------------------ Epoch 452 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.115501 - Iter 028 / 029, Loss: 0.050829 * Train accuracy / confusion: 96.12% / [[347, 17], [19, 545]], * Val accuracy / confusion: 65.59% / [[125, 105], [98, 262]] ------------------------------ Epoch 453 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.047655 - Iter 028 / 029, Loss: 0.079629 * Train accuracy / confusion: 93.32% / [[333, 28], [34, 533]], * Val accuracy / confusion: 68.14% / [[133, 97], [91, 269]] ------------------------------ Epoch 454 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.174648 - Iter 028 / 029, Loss: 0.158397 * Train accuracy / confusion: 95.26% / [[343, 22], [22, 541]], * Val accuracy / confusion: 66.78% / [[132, 98], [98, 262]] ------------------------------ Epoch 455 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.030240 - Iter 028 / 029, Loss: 0.227123 * Train accuracy / confusion: 96.34% / [[341, 18], [16, 553]], * Val accuracy / confusion: 67.97% / [[138, 92], [97, 263]] ------------------------------ Epoch 456 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.073953 - Iter 028 / 029, Loss: 0.128817 * Train accuracy / confusion: 96.12% / [[347, 16], [20, 545]], * Val accuracy / confusion: 68.64% / [[129, 101], [84, 276]] ------------------------------ Epoch 457 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.146884 - Iter 028 / 029, Loss: 0.063756 * Train accuracy / confusion: 95.47% / [[350, 12], [30, 536]], * Val accuracy / confusion: 68.64% / [[133, 97], [88, 272]] ------------------------------ Epoch 458 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.178239 - Iter 028 / 029, Loss: 0.234102 * Train accuracy / confusion: 95.91% / [[341, 17], [21, 549]], * Val accuracy / confusion: 67.80% / [[139, 91], [99, 261]] ------------------------------ Epoch 459 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.034874 - Iter 028 / 029, Loss: 0.179232 * Train accuracy / confusion: 96.77% / [[343, 17], [13, 555]], * Val accuracy / confusion: 71.19% / [[138, 92], [78, 282]] ------------------------------ Epoch 460 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.139736 - Iter 028 / 029, Loss: 0.029849 * Train accuracy / confusion: 95.80% / [[345, 19], [20, 544]], * Val accuracy / confusion: 67.12% / [[126, 104], [90, 270]] ------------------------------ Epoch 461 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.184993 - Iter 028 / 029, Loss: 0.046089 * Train accuracy / confusion: 95.37% / [[341, 23], [20, 544]], * Val accuracy / confusion: 69.49% / [[126, 104], [76, 284]] ------------------------------ Epoch 462 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.091869 - Iter 028 / 029, Loss: 0.136981 * Train accuracy / confusion: 95.47% / [[341, 22], [20, 545]], * Val accuracy / confusion: 69.15% / [[137, 93], [89, 271]] ------------------------------ Epoch 463 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.128592 - Iter 028 / 029, Loss: 0.180212 * Train accuracy / confusion: 96.88% / [[351, 12], [17, 548]], * Val accuracy / confusion: 69.49% / [[133, 97], [83, 277]] ------------------------------ Epoch 464 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.088563 - Iter 028 / 029, Loss: 0.133423 * Train accuracy / confusion: 96.12% / [[345, 17], [19, 547]], * Val accuracy / confusion: 69.49% / [[132, 98], [82, 278]] ------------------------------ Epoch 465 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.227797 - Iter 028 / 029, Loss: 0.193109 * Train accuracy / confusion: 95.69% / [[341, 22], [18, 547]], * Val accuracy / confusion: 70.34% / [[137, 93], [82, 278]] ------------------------------ Epoch 466 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.038736 - Iter 028 / 029, Loss: 0.035798 * Train accuracy / confusion: 96.01% / [[345, 17], [20, 546]], * Val accuracy / confusion: 68.81% / [[136, 94], [90, 270]] ------------------------------ Epoch 467 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.027401 - Iter 028 / 029, Loss: 0.173052 * Train accuracy / confusion: 95.37% / [[348, 17], [26, 537]], * Val accuracy / confusion: 70.00% / [[141, 89], [88, 272]] ------------------------------ Epoch 468 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.070569 - Iter 028 / 029, Loss: 0.293686 * Train accuracy / confusion: 95.26% / [[338, 23], [21, 546]], * Val accuracy / confusion: 67.29% / [[133, 97], [96, 264]] ------------------------------ Epoch 469 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.132061 - Iter 028 / 029, Loss: 0.171037 * Train accuracy / confusion: 96.44% / [[343, 16], [17, 552]], * Val accuracy / confusion: 68.14% / [[135, 95], [93, 267]] ------------------------------ Epoch 470 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.151103 - Iter 028 / 029, Loss: 0.260848 * Train accuracy / confusion: 96.12% / [[346, 16], [20, 546]], * Val accuracy / confusion: 67.29% / [[130, 100], [93, 267]] ------------------------------ Epoch 471 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.102812 - Iter 028 / 029, Loss: 0.051766 * Train accuracy / confusion: 95.80% / [[343, 18], [21, 546]], * Val accuracy / confusion: 67.29% / [[139, 91], [102, 258]] ------------------------------ Epoch 472 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.128959 - Iter 028 / 029, Loss: 0.093581 * Train accuracy / confusion: 96.01% / [[343, 18], [19, 548]], * Val accuracy / confusion: 70.17% / [[146, 84], [92, 268]] ------------------------------ Epoch 473 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.027948 - Iter 028 / 029, Loss: 0.062456 * Train accuracy / confusion: 96.12% / [[344, 18], [18, 548]], * Val accuracy / confusion: 70.17% / [[141, 89], [87, 273]] ------------------------------ Epoch 474 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.079242 - Iter 028 / 029, Loss: 0.039042 * Train accuracy / confusion: 95.80% / [[345, 17], [22, 544]], * Val accuracy / confusion: 68.14% / [[139, 91], [97, 263]] ------------------------------ Epoch 475 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.025607 - Iter 028 / 029, Loss: 0.044385 * Train accuracy / confusion: 97.31% / [[349, 13], [12, 554]], * Val accuracy / confusion: 69.15% / [[134, 96], [86, 274]] ------------------------------ Epoch 476 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.084146 - Iter 028 / 029, Loss: 0.068546 * Train accuracy / confusion: 95.58% / [[341, 21], [20, 546]], * Val accuracy / confusion: 67.80% / [[132, 98], [92, 268]] ------------------------------ Epoch 477 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.040945 - Iter 028 / 029, Loss: 0.099209 * Train accuracy / confusion: 96.34% / [[348, 16], [18, 546]], * Val accuracy / confusion: 67.97% / [[133, 97], [92, 268]] ------------------------------ Epoch 478 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.072418 - Iter 028 / 029, Loss: 0.107717 * Train accuracy / confusion: 95.80% / [[345, 18], [21, 544]], * Val accuracy / confusion: 70.00% / [[133, 97], [80, 280]] ------------------------------ Epoch 479 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.150617 - Iter 028 / 029, Loss: 0.079746 * Train accuracy / confusion: 95.37% / [[341, 20], [23, 544]], * Val accuracy / confusion: 68.64% / [[133, 97], [88, 272]] ------------------------------ Epoch 480 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.186572 - Iter 028 / 029, Loss: 0.119531 * Train accuracy / confusion: 95.15% / [[341, 23], [22, 542]], * Val accuracy / confusion: 67.80% / [[123, 107], [83, 277]] ------------------------------ Epoch 481 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.051727 - Iter 028 / 029, Loss: 0.077782 * Train accuracy / confusion: 95.91% / [[348, 17], [21, 542]], * Val accuracy / confusion: 68.31% / [[131, 99], [88, 272]] ------------------------------ Epoch 482 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.058730 - Iter 028 / 029, Loss: 0.098556 * Train accuracy / confusion: 96.01% / [[347, 17], [20, 544]], * Val accuracy / confusion: 67.97% / [[140, 90], [99, 261]] ------------------------------ Epoch 483 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.209312 - Iter 028 / 029, Loss: 0.054987 * Train accuracy / confusion: 95.58% / [[342, 20], [21, 545]], * Val accuracy / confusion: 68.14% / [[139, 91], [97, 263]] ------------------------------ Epoch 484 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.042597 - Iter 028 / 029, Loss: 0.180206 * Train accuracy / confusion: 96.01% / [[346, 18], [19, 545]], * Val accuracy / confusion: 70.00% / [[135, 95], [82, 278]] ------------------------------ Epoch 485 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.134356 - Iter 028 / 029, Loss: 0.029426 * Train accuracy / confusion: 95.58% / [[343, 21], [20, 544]], * Val accuracy / confusion: 68.31% / [[138, 92], [95, 265]] ------------------------------ Epoch 486 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.125447 - Iter 028 / 029, Loss: 0.030007 * Train accuracy / confusion: 95.80% / [[343, 21], [18, 546]], * Val accuracy / confusion: 68.31% / [[137, 93], [94, 266]] ------------------------------ Epoch 487 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.154751 - Iter 028 / 029, Loss: 0.130918 * Train accuracy / confusion: 96.23% / [[346, 16], [19, 547]], * Val accuracy / confusion: 67.63% / [[132, 98], [93, 267]] ------------------------------ Epoch 488 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.366435 - Iter 028 / 029, Loss: 0.044555 * Train accuracy / confusion: 95.91% / [[345, 19], [19, 545]], * Val accuracy / confusion: 68.64% / [[132, 98], [87, 273]] ------------------------------ Epoch 489 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.026684 - Iter 028 / 029, Loss: 0.120974 * Train accuracy / confusion: 96.34% / [[343, 19], [15, 551]], * Val accuracy / confusion: 69.15% / [[140, 90], [92, 268]] ------------------------------ Epoch 490 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.086689 - Iter 028 / 029, Loss: 0.108821 * Train accuracy / confusion: 95.91% / [[343, 17], [21, 547]], * Val accuracy / confusion: 69.32% / [[137, 93], [88, 272]] ------------------------------ Epoch 491 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.098474 - Iter 028 / 029, Loss: 0.075248 * Train accuracy / confusion: 96.12% / [[342, 17], [19, 550]], * Val accuracy / confusion: 67.46% / [[138, 92], [100, 260]] ------------------------------ Epoch 492 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.150741 - Iter 028 / 029, Loss: 0.028571 * Train accuracy / confusion: 95.58% / [[342, 21], [20, 545]], * Val accuracy / confusion: 67.46% / [[136, 94], [98, 262]] ------------------------------ Epoch 493 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.051815 - Iter 028 / 029, Loss: 0.098035 * Train accuracy / confusion: 96.01% / [[345, 19], [18, 546]], * Val accuracy / confusion: 67.63% / [[133, 97], [94, 266]] ------------------------------ Epoch 494 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.100851 - Iter 028 / 029, Loss: 0.057548 * Train accuracy / confusion: 95.80% / [[343, 19], [20, 546]], * Val accuracy / confusion: 67.29% / [[129, 101], [92, 268]] ------------------------------ Epoch 495 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.049827 - Iter 028 / 029, Loss: 0.069832 * Train accuracy / confusion: 96.66% / [[348, 14], [17, 549]], * Val accuracy / confusion: 69.32% / [[141, 89], [92, 268]] ------------------------------ Epoch 496 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.264310 - Iter 028 / 029, Loss: 0.116756 * Train accuracy / confusion: 95.47% / [[345, 19], [23, 541]], * Val accuracy / confusion: 68.47% / [[128, 102], [84, 276]] ------------------------------ Epoch 497 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.161066 - Iter 028 / 029, Loss: 0.034416 * Train accuracy / confusion: 96.66% / [[345, 15], [16, 552]], * Val accuracy / confusion: 65.93% / [[126, 104], [97, 263]] ------------------------------ Epoch 498 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.164108 - Iter 028 / 029, Loss: 0.346033 * Train accuracy / confusion: 95.26% / [[340, 21], [23, 544]], * Val accuracy / confusion: 70.34% / [[141, 89], [86, 274]] ------------------------------ Epoch 499 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.057385 - Iter 028 / 029, Loss: 0.142656 * Train accuracy / confusion: 95.80% / [[339, 18], [21, 550]], * Val accuracy / confusion: 65.59% / [[127, 103], [100, 260]] ------------------------------ Epoch 500 / 500, Learning rate: 1.49e-06 ------------------------------ - Iter 014 / 029, Loss: 0.063247 - Iter 028 / 029, Loss: 0.294175 * Train accuracy / confusion: 96.77% / [[348, 15], [15, 550]], * Val accuracy / confusion: 66.61% / [[127, 103], [94, 266]] **************************************** Training Ends ****************************************
- Test accuracy (last model): 69.11% - Confusion matrix (last model): [[ 961 449] [ 663 1527]]
- Test accuracy (best model): 73.25% - Confusion matrix (best model): [[ 867 543] [ 420 1770]]
# checkpoint save path
if save_checkpoint:
os.makedirs('checkpoint/', exist_ok=True)
today = datetime.date.today()
torch.save(best_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_TinyResNet_best')
torch.save(last_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_TinyResNet_last')
print('- Debug table:')
pprint.pp(last_test_debug, indent=2, width=100)
- Debug table:
{ '01183': {'GT': 1, 'Acc': ' 53.33%', 'Pred': [14, 16], 'edfname': '01303198_020317'},
'00697': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00983533_290618'},
'00825': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01129445_130220'},
'00504': {'GT': 0, 'Acc': ' 6.67%', 'Pred': [2, 28], 'edfname': '00813343_041218'},
'00192': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '00608961_131118'},
'00134': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '00446328_171116'},
'00741': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '01025734_280715'},
'00206': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00616193_090218'},
'01231': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01334787_211117'},
'00793': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '01086373_020615'},
'01045': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01235281_191015'},
'00407': {'GT': 1, 'Acc': ' 53.33%', 'Pred': [14, 16], 'edfname': '00740694_110315'},
'00669': {'GT': 1, 'Acc': ' 23.33%', 'Pred': [23, 7], 'edfname': '00957862_230317'},
'00843': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01135545_230715'},
'00029': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00164098_180919'},
'00299': {'GT': 0, 'Acc': ' 70.00%', 'Pred': [21, 9], 'edfname': '00671212_160819'},
'00702': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '00985987_180518'},
'01069': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01243158_301115'},
'00913': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01151967_160414'},
'01307': {'GT': 0, 'Acc': ' 6.67%', 'Pred': [2, 28], 'edfname': '01376302_060718'},
'00638': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00941649_111218'},
'00286': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '00663561_030414'},
'00954': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '01178797_240914'},
'00587': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '00894185_250817'},
'00542': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '00852650_170818'},
'00996': {'GT': 1, 'Acc': ' 46.67%', 'Pred': [16, 14], 'edfname': '01204692_120315'},
'00403': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00739162_011215'},
'00408': {'GT': 0, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '00740750_110315'},
'00078': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00324958_271118'},
'00277': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00657017_281218'},
'00671': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00958455_200917'},
'01066': {'GT': 0, 'Acc': ' 46.67%', 'Pred': [14, 16], 'edfname': '01242983_071215'},
'00965': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '01186214'},
'01125': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01276737_300616'},
'00227': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00626957_071217'},
'00531': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00840844_250119'},
'00088': {'GT': 1, 'Acc': ' 33.33%', 'Pred': [20, 10], 'edfname': '00344923_021116'},
'00267': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '00650465_160318'},
'00069': {'GT': 1, 'Acc': ' 60.00%', 'Pred': [12, 18], 'edfname': '00307906_230617'},
'00365': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00712852_060418'},
'00991': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01203444_090819'},
'00815': {'GT': 0, 'Acc': ' 66.67%', 'Pred': [20, 10], 'edfname': '01125477_030918'},
'01351': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01409497_111219'},
'00065': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00293228_070918'},
'00952': {'GT': 1, 'Acc': ' 26.67%', 'Pred': [22, 8], 'edfname': '01178672_300518'},
'00124': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00418981_060116'},
'00854': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01138301_230114'},
'00472': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00784418_201016'},
'01258': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01348039_181017'},
'01375': {'GT': 1, 'Acc': ' 36.67%', 'Pred': [19, 11], 'edfname': '01429374_230519'},
'00885': {'GT': 0, 'Acc': ' 23.33%', 'Pred': [7, 23], 'edfname': '01142810_180214'},
'00917': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '01154159_230414'},
'00938': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '01161826_050916'},
'00881': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01141790_190214'},
'00096': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00369252_131216'},
'01075': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01250004_260116'},
'01165': {'GT': 0, 'Acc': ' 3.33%', 'Pred': [1, 29], 'edfname': '01296533_281116'},
'01067': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '01242984_211215'},
'00828': {'GT': 1, 'Acc': ' 56.67%', 'Pred': [13, 17], 'edfname': '01131959_310118'},
'01337': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01400560_160419'},
'00383': {'GT': 1, 'Acc': ' 56.67%', 'Pred': [13, 17], 'edfname': '00723110_240419'},
'00900': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '01147100'},
'01336': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '01398060_050918'},
'01115': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01271298_270319'},
'00667': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '00956561_241116'},
'00439': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00760780_141118'},
'00369': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '00715828_111016'},
'00955': {'GT': 1, 'Acc': ' 40.00%', 'Pred': [18, 12], 'edfname': '01178888_161117'},
'00300': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00671379_290617'},
'01196': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '01307883_100217'},
'00923': {'GT': 0, 'Acc': ' 3.33%', 'Pred': [1, 29], 'edfname': '01155730_070514'},
'00058': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '00285244_020414'},
'00584': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '00891889_060717'},
'00749': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01027623_260916'},
'01334': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01396872_021018'},
'00588': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00895530_090616'},
'00679': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00963069_150618'},
'00385': {'GT': 0, 'Acc': ' 13.33%', 'Pred': [4, 26], 'edfname': '00723232_270318'},
'00018': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00128526_180817'},
'01281': {'GT': 1, 'Acc': ' 66.67%', 'Pred': [10, 20], 'edfname': '01358607_280918'},
'00651': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00951808_251116'},
'01253': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01344212_240817'},
'01035': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01231654_260417'},
'00551': {'GT': 1, 'Acc': ' 43.33%', 'Pred': [17, 13], 'edfname': '00865039_170816'},
'00870': {'GT': 0, 'Acc': ' 23.33%', 'Pred': [7, 23], 'edfname': '01139947_120214'},
'00578': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00888613_080618'},
'00730': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '01011922_270815'},
'00516': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00823206_130514'},
'01330': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01392885_240718'},
'00944': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01168853_070316'},
'00125': {'GT': 0, 'Acc': ' 60.00%', 'Pred': [18, 12], 'edfname': '00418981_090316'},
'00508': {'GT': 0, 'Acc': ' 66.67%', 'Pred': [20, 10], 'edfname': '00817022_010415'},
'01317': {'GT': 1, 'Acc': ' 43.33%', 'Pred': [17, 13], 'edfname': '01381606_160518'},
'00608': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '00907971_030217'},
'00471': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '00784417_100315'},
'00821': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01128393_300715'},
'00122': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00416942_190516'},
'01007': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01211467_070415'},
'01247': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01339759_310717'},
'00173': {'GT': 1, 'Acc': ' 63.33%', 'Pred': [11, 19], 'edfname': '00601028_290618'},
'01026': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01225123_050815'},
'01018': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01216443_240518'},
'00418': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00745209_220916'},
'01206': {'GT': 1, 'Acc': ' 3.33%', 'Pred': [29, 1], 'edfname': '01314786_200317'},
'01215': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01321744_130417'},
'01105': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '01266696_110516'},
'00598': {'GT': 1, 'Acc': ' 60.00%', 'Pred': [12, 18], 'edfname': '00899964_110414'},
'00851': {'GT': 0, 'Acc': ' 6.67%', 'Pred': [2, 28], 'edfname': '01138297_230114'},
'01138': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '01281605_070716'},
'00079': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '00325929_170119'},
'00245': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00637371_050917'},
'00591': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '00896386_240914'},
'00329': {'GT': 0, 'Acc': ' 30.00%', 'Pred': [9, 21], 'edfname': '00685248_150414'},
'00272': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '00651389_281016'},
'00176': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '00602435_270217'},
'00807': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '01112291_231115'},
'00271': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '00651252_140618'},
'00712': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00988278_210915'},
'00974': {'GT': 1, 'Acc': ' 33.33%', 'Pred': [20, 10], 'edfname': '01193508_171214'},
'01163': {'GT': 1, 'Acc': ' 6.67%', 'Pred': [28, 2], 'edfname': '01296342_141116'}}
signal_headers = ['Fp1-AVG', 'F3-AVG', 'C3-AVG', 'P3-AVG',
'O1-AVG', 'Fp2-AVG', 'F4-AVG', 'C4-AVG',
'P4-AVG', 'O2-AVG', 'F7-AVG', 'T3-AVG',
'T5-AVG', 'F8-AVG', 'T4-AVG', 'T6-AVG',
'FZ-AVG', 'CZ-AVG', 'PZ-AVG', 'EKG']
from scipy.ndimage.filters import gaussian_filter1d
def jitter(X, amount):
left = X[:, :, :-amount]
right = X[:, :, -amount:]
X = torch.cat([left, right], dim=2)
return X
def blur_signal(X, sigma=1):
X_np = X.cpu().clone().numpy()
X_np = gaussian_filter1d(X_np, sigma, axis=2)
X.copy_(torch.Tensor(X_np).type_as(X))
return X
def create_class_visualization(target_y, model, dtype, **kwargs):
"""
Generate an image to maximize the score of target_y under a pretrained model.
Inputs:
- target_y: Integer in the range [0, 1000) giving the index of the class
- model: A pretrained CNN that will be used to generate the image
- dtype: Torch datatype to use for computations
Keyword arguments:
- l2_reg: Strength of L2 regularization on the image
- learning_rate: How big of a step to take
- num_iterations: How many iterations to use
- blur_every: How often to blur the image as an implicit regularizer
- max_jitter: How much to gjitter the image as an implicit regularizer
- show_every: How often to show the intermediate result
"""
model.type(dtype)
l2_reg = kwargs.pop('l2_reg', 1e-3)
learning_rate = kwargs.pop('learning_rate', 25)
num_iterations = kwargs.pop('num_iterations', 15000)
blur_every = kwargs.pop('blur_every', 10)
max_jitter = kwargs.pop('max_jitter', 100)
show_every = kwargs.pop('show_every', 5000)
# Randomly initialize the image as a PyTorch Tensor, and make it requires gradient.
signal = torch.randn(2, *train_dataset[0]['signal'].shape).mul_(1.0).type(dtype).requires_grad_().to(device)
blur_signal(signal.data, sigma=3)
for t in tqdm(range(num_iterations)):
# Randomly jitter the image a bit; this gives slightly nicer results
jittering = random.randint(0, max_jitter)
signal.data.copy_(jitter(signal.data, jittering))
# run the model
age = torch.tensor([age_mean, age_mean], dtype=torch.float32).to(device)
scores = model(signal, age)
# score loss and L-2 regularization
loss = scores[:, target_y] - l2_reg * torch.norm(signal)
loss = loss.sum()
# compute the gradients on the image
loss.backward()
with torch.no_grad():
# gradient ascent
signal += learning_rate * signal.grad
# manually zero the gradients after running the backward pass
signal.grad.zero_()
# Undo the random jitter
signal.data.copy_(jitter(signal.data, -jittering))
# As regularizer, periodically blur the image
if t % blur_every == 0:
blur_signal(signal.data, sigma=1)
# Periodically show the signal
if t == 0 or (t + 1) % show_every == 0 or t == num_iterations - 1:
fig = plt.figure(num=1, clear=True,
figsize=(15.0, 10.0), constrained_layout=True)
for s in range(signal.shape[0]):
ax = fig.add_subplot(signal.shape[0], 1, s + 1)
sig = signal[s].data.clone().cpu()
for (k, h) in enumerate(signal_headers):
ax.plot(np.arange(sig.shape[1]) / 200, sig[k], label=h)
class_name = class_label_to_type[target_y]
plt.legend(shadow=True).get_frame().set_facecolor('white')
plt.title('%s\nIteration %d / %d' % (class_name, t + 1, num_iterations))
plt.show()
fig.clear()
plt.close(fig)
return signal
#dtype = torch.FloatTensor
dtype = torch.cuda.FloatTensor # Uncomment this to use GPU
model.type(dtype)
target_y = 0 # Normal, NV-MCI, NV-Dementia
out = create_class_visualization(target_y, model, dtype)
age = torch.tensor([age_mean, age_mean], dtype=torch.float32).to(device)
scores = model(out, age)
pred = F.log_softmax(scores, dim=1)
estimation = pred.argmax(dim=-1)
print(scores)
print(pred)
print(estimation)
tensor([[ 482.8104, -203.5646],
[ 484.6816, -206.3222]], device='cuda:0', grad_fn=<AddmmBackward>)
tensor([[ 0.0000, -686.3750],
[ 0.0000, -691.0038]], device='cuda:0', grad_fn=<LogSoftmaxBackward>)
tensor([0, 0], device='cuda:0')